Using data to succeed: tools for machine learning

Business Impact - Using data to succeed: tools for machine learning

Using data to succeed: tools for machine learning

Business Impact - Using data to succeed: tools for machine learning
Business Impact - Using data to succeed: tools for machine learning

How can business leaders collaborate productively and effectively with data science teams? Winning with Data Science takes a narrative approach with fictitious characters to showcase different approaches to projects involving data science teams. In this excerpt, David is a senior data scientist working for Stardust Health Insurance, a medium-sized insurance company working primarily in California and Florida. David works closely with Kamala, a rising star at the company who has both an MD and an MBA and, most importantly for our story, a keen interest in using data to succeed.

Examining residuals

“I’d like to welcome you all to the inaugural Stardust Health Insurance data science team hackathon.”

David was having fun as the emcee of the event. “Our teams have been hard at work to optimise our model to predict healthcare expenditure for patients with back pain who receive nonsurgical treatment. Before we get started, let’s recap the current state of our model.

“The outcome for this model was predicted back pain–related healthcare expenditure in the year following a request for prior authorisation. On average, the absolute difference between the model’s predicted healthcare expenditure and the true healthcare expenditure was USD$12,000 for the first year following the prior authorisation request. The actual differences ranged from $50 to $50,000.

“Those on the prior authorisation team have been using this model for the past several months with success: they are seeing reduced healthcare expenditure as a result of their prior authorisation decisions and initial analyses show improvements in patient outcomes as well. Although the model was designed to predict expenditures for two years, these initial results are promising and now we want to see how well we can improve the performance of this model.

“The first team we will be hearing from didn’t change the model architecture: the team members used linear regression, but they did some clever analysis to figure out how to improve the model. I’ll hand it over to them.”

The team lead walked to the front of the room and flashed their slides on the screen. “The performance of the original model was good, but we felt that there was still more that could be done within the confines of linear regression. We decided to do a deep dive into what types of patients the model performs well on and what types of patients it doesn’t perform as well on. To do this, we examined the residuals.”

The team lead continued: “What we found was that some patients have very small residuals, but for other patients, the model performed very poorly – on average, the model was off by more than $25,000. We ran some descriptive statistics to see whether those groups of patients were different in any meaningful way. What we found is that the patients with higher residuals tend to have jobs that involve more manual labour – for example, farming or construction. So instead of changing the model architecture, we decided to add more features regarding a patient’s job.

“When we added in these new features, we saw that the residuals for the previously poor-performing group dropped from $25,000 to $15,000. In other words, we were able to improve the performance of our model for that group of patients by about 40 per cent. Just adding a few well-selected features , we were able to bring down the average residual from $12,000 to $9,000.”

Interaction terms and transformations

David took the mic and welcomed the next team: “The next team also stuck with linear regression but took a clever approach to feature engineering.”

The team lead took to the stage and said: “We also felt that the biggest limitation of our model was its features. It doesn’t matter if you use linear regression, random forest, or a neural network; if your features aren’t good, your predictions won’t be good. So we decided to engineer new features using the ones that we already had.”

One of the simplest approaches to automated feature engineering is calculating interaction terms. An interaction term represents the relationship between two main terms. For example, patient age and patient gender may be included in the original healthcare expenditure model as main effects. But what if the relationship between healthcare spending and age depends on sex?

We can add an interaction term by including the product of age multiplied by gender as a new feature in our model. This interaction term allows for different slopes for the relationship between expenditure and age for men versus women.

The team lead summed up the results: “By including all possible two-way interaction terms, we gave our model access to relationships between variables that we hadn’t considered including in the original model. We were able to bring the average residual down to $8,000!”

K-nearest neighbours

“This next team moved away from linear regression and tried out a different model architecture,” said David, as he stepped down from the stage.

The team lead picked up the mic: “One characteristic of linear regression is that it uses all the data points in the dataset to make a prediction. This can be good in some cases, but we thought it might be better to use an approach where the prediction is based on only the handful of data points that are most similar to the patient in question. Therefore, we used a ‘K-nearest neighbour’ (K-NN) regression model.”

The first step of the modelling process is to choose the parameter ‘K’, which represents the number of observations the model will use to make a prediction. For example, if K=20, the model will look at the 20 data points that are most similar to the data point it is making a prediction from. The next step is to determine how to define ‘similar’. The most common approach is to calculate the Euclidean distance between datapoints. This amounts to adding the squares of the distance in each dimension (for text variables, Hamming distance is often used).

The team lead went on. “We determined through cross-validation that the optimal value for K was 100. Simply put, our model makes predictions for new patients by averaging the expenditures of the 100 most similar patients in the dataset.” For categorical outcomes, K-NN finds the K observations that are closest to the datapoint and assigns the predicted value to the class with the most votes.

Another consideration is what features you should include in K-NN. You want to use only features that are relevant in predicting the outcome of interest. Often, there must be some filtering of input variables to first remove the ones that aren’t predictive. The features then need to be normalised so each feature has about the same range. If you don’t normalise the features, then those that have a much larger range will dominate the distance computation, and other features with smaller ranges won’t contribute much to the modelling.

The team lead concluded: “One of the advantages of K-NN is that it can make predictions for nonlinear relationships because it makes no assumptions about linearity. The model reduced the average residuals from $12,000 to $10,000 which is not as big an improvement as our colleagues. But our team’s guess is that K-NN performed better on the patients who were harder for linear regression to predict.”

Decision trees

The next team lead took to the stage. “Similar to the last group, we wanted to account for possible nonlinear relationships between variables. We also wanted the output of the model to correspond to easily interpretable patient profiles. A regression tree model was the perfect choice for our goals.”

Classification and regression tree (CART) modelling consists of dividing the population into smaller subpopulations and then making predictions on those smaller subpopulations.

For example, assume we’re building a regression tree that splits the population into two groups for each node. To predict healthcare expenditure, the algorithm would find the best variable and value of that variable to separate out the high- and low-cost patients. Once this first split is done, there are now two groups, the low- and the high-cost patients. The algorithm is then applied to each of these two groups to again find the best variable and value of that variable to split each of these groups into two more groups, so there are now four groups. The algorithm will stop when there are not enough customers in each group to split again or when it reaches some other stopping rule. When the CART model is completed, the entire population will be assigned to one and only one group, called a leaf, and the characteristics of each leaf can be easily read.

For example, the highest-cost leaf may be male patients over 65 years old who live in the US Northeast, and the lowest-cost leaf may be female patients under 18 who live in the South. A prediction for a new patient would be made by identifying what leaf the customer belongs to and assigning the average value of that leaf to that customer.

CART modelling has several advantages. First, the data scientist does not have to make assumptions about the features and their supposed relationship with the outcome; only the splitting and stopping rules need to be defined for the tree to be produced. Second, CART models can be used to predict binomial variables, categorical variables and continuous variables, and they are not as sensitive to outliers and missing data as other regression methods are. Third, CART models can easily represent nonlinear relationships and interaction terms without the need for the modeler to specify them in the model itself. Lastly, CART modelling is easily interpretable in that it produces subpopulations of high and low values based on a set of if/then statements, allowing you easily to look at the rules and ask if they make sense.

The team lead summarised the results. “Our tree-based model didn’t reduce the average residual by much: we went from $12,000 to $11,000. But we discovered we could develop this tree-based model much more quickly than we did using the original model because the data did not require much pre-processing. Since tree-based models can handle missing values and variables of very different scales, it’s relatively quick to train a model once you have the data collected.”

Boosting, bagging and ensembling

David clapped for the last team and went back up on stage. “Now that we’ve heard from all our teams, I want to present a surprise that the data team leaders have been working on since the end of the hackathon. We’ve all heard the old saying ‘two heads are better than one’. But have you heard the more recent saying ‘two machine learning models are better than one’?” The audience laughed.

“After all the teams submitted their models, we had a secret team working in the background to combine all the models into a single, more accurate and more robust prediction using ensembling methods. ”

One of the most common ensembling methods is stacking. In model stacking, different models are created and then used as input variables to a new model, which is used to make the final prediction. The first models are known as level one models and these level one model predictions serve as inputs to the level two model. Stacked models can be thought of as a method to weight different models to produce a final result. The level two model, also called the ‘stacked model’, can outperform each of the individual models by more heavily weighting the level one models where they perform best and giving those models less weight where they perform poorly.

A special case of ensembling is called ‘bootstrap aggregation’ or ‘bagging’ for short. Bootstrapping refers to making several datasets from the original dataset by resampling observations. For example, from a starting dataset of 1,000 observations, you may create 10 bootstrapped datasets, each containing 1,000 observations resampled from the original 1,000. A model is fitted to each of the bootstrapped datasets and the resulting predictions are aggregated. It has been shown that bagging can improve prediction accuracy and help avoid overfitting.

Another technique commonly used to improve the performance of machine learning models is gradient boosted machine learning, also known as GBML. The word ‘boosted’ is critical here. Boosting involves having models learn by giving the misclassified observations more weight in the next iteration of the training, as well as by potentially giving more weight to the more accurate trees. There are many boosting algorithms; two of the most commonly used are Adaboost and Arcboost.

David continued: “We gave each model access to all the features that were engineered by the different teams and we applied bagging and boosting to the regression tree model to improve its performance. Finally, we developed a stacked model, which combined the predictions from the three level one models using a level two linear regression model. Our stacked ensemble vastly outperformed each of the individual models: we were able to decrease the average residual from $12,000 to $5,000.”

Kamala was floored. How could the stacked model be that much better? “David, I’m wondering how the stacked model performed so well,” she said. “Before the ensembling, the best model was one of the linear regression models that had an average residual of $8,000. All the other models had residuals higher than that. How is it that adding a model with residuals over $10,000 to a model with residuals at $8,500 leads to a model with residuals at $5,000?”

“That’s the beauty of ensembling,” David replied. “Imagine you’re on a trivia game show with a partner. Your partner is a quiz bowl whiz. They know just about everything – except they’ve never had a penchant for pop music, so they’re completely useless when it comes to any question relating to music. You, on the other hand, know absolutely nothing about geography, sports, science, or history. But you’re a huge music and film fan, so any question on pop music that comes your way is a piece of cake. Individually, your partner would perform way better than you. They may get 90 per cent of all questions right if you assume the remaining 10 per cent are about music. You, on the other hand, would do terribly on your own. You’d be lucky to get 15 per cent if you assume those are the questions about music and films. Now, what if we put you two together on the same team? You can complement your partner’s knowledge on music and films and they can carry the team for all the remaining questions. Individually, it’s unlikely either of you would get 100 per cent, but together you have a real shot at a perfect score.”

This made sense to Kamala. “It’s like forming a committee. The different backgrounds of the committee members complement each other and, collectively, they’re able to make a better decision than they would individually.”

“Exactly,” David concluded. “Two models are better than one.”

Headline image credit: Google DeepMind on Unsplash

Excerpted from Winning with Data Science by Howard Steven Friedman and Akshay Swaminathan, published by Columbia Business School Publishing. Copyright (c) 2024 Howard Steven Friedman and Akshay Swaminathan. Used by arrangement with the Publisher. All rights reserved. Further information is available at winningwithdatascience.com.

Howard Steven Friedman is an adjunct professor at Columbia University and a data scientist with decades of experience leading analytics projects in the private and public sectors.
Akshay Swaminathan is a data scientist who works on strengthening health systems and currently leads the data science team at Cerebral. He is also a Knight-Hennessy scholar at Stanford University School of Medicine.

Get an exclusive 20% discount on a copy of Winning with Data Science, courtesy of the BGA Book Club.

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Learning beyond the books: the impact of AR and VR on business education

Business Impact: Learning beyond the books: the impact of AR and VR on business education

Learning beyond the books: the impact of AR and VR on business education

Business Impact: Learning beyond the books: the impact of AR and VR on business education
Business Impact: Learning beyond the books: the impact of AR and VR on business education

In the constantly changing field of education, cutting-edge methods that use technology to empower and engage students are replacing traditional lectures and textbooks. Virtual reality (VR) and augmented reality (AR) have become transformative tools among these ground-breaking innovations, especially in the field of business education.

This article explores how AR and VR are changing the way business concepts are learned, retained and used by offering immersive, interactive and hands-on learning experiences that go far beyond the boundaries of textbooks.

The current state of business education

Business education has been based on traditional means of instruction – textbooks, lectures, case studies, static presentations and so on. While these approaches are fundamental, they frequently fail to completely engage students and prepare them for the fast-paced, dynamic business environment.

Increasingly, business school students struggle to stay interested in traditional methods of education because they find them boring. In addition, these forms of passive learning do not always encourage critical thinking, problem-solving techniques, or practical experience directly, leading to poor idea memory and application.

More creative and interactive teaching strategies that better meet the needs of the contemporary corporate world are therefore required to solve these issues. In this, AR and VR technologies offer the chance to close the knowledge gap between theory and practice.

Understanding AR and VR

AR superimposes digital data over the physical world, such as pictures, movies, or three-dimensional (3D) models. By incorporating digital components into reality, AR improves the user’s view of it. Conversely, VR technology submerges people into a fully digital realm, frequently using headgear or other equipment to establish a sensation of presence within a computer-generated environment.

The degree of immersion is where AR and VR differ most from one another. While VR produces a totally realistic, simulated experience where the user is momentarily detached from their physical surroundings, AR enriches the real world.

Hardware and software are combined to power AR and VR technologies. They are being used more often in education to provide dynamic, participatory and hands-on learning environments. AR is helpful for on-site training and visualisation because it adds digital material to real-world events. Conversely, VR works well for immersive simulations, allowing students to investigate situations that may otherwise be unavailable or difficult to experience in the real world. Thanks to their ability to stimulate the senses and encourage active engagement, these technologies have the potential to greatly improve the educational experience.

Five beneficial applications of AR and VR in business education

1) Enhanced motivation and engagement: Compared to traditional teaching techniques, AR) and VR can provide students with immersive and interactive learning experiences that are significantly more motivating and engaging. For instance, the Marshall School of Business at the University of Southern California employs VR technology to create realistic case studies that allow students to apply their knowledge in an environment that closely mimics the real world. Similarly, the AI Research Centre at Woxsen University’s School of Business has trained 60 to 70 faculty members to deliver complex course materials within the Woxsen metaverse environment, with the aim of benefiting more than 2,000 students.

2) Improved learning outcomes: Research has indicated that the use of AR and VR in education can result in superior learning outcomes, including better exam and assessment scores and an improvement in knowledge retention. In research from the University of Central Florida, for example, students who learned accounting concepts using VR performed better in a subsequent exam than those who used traditional teaching techniques alone.

3) Enhanced soft skills development: Students can enhance critical soft skill areas, such as problem-solving, teamwork and communication, with the help of AR and VR. For instance, the University of Pennsylvania’s Wharton School simulates job interviews using VR, giving students the chance to hone their communication skills and get input from peers and teachers.

4) Reduced training costs: By removing the need for expensive tools and supplies, AR and VR can assist in lowering the cost of training. Walmart, for instance, trains staff members on how to operate the company’s new self-checkout machines using VR. Estimates suggest that Walmart has saved millions of dollars in training expenses as a result.

5) Increased safety: Students can receive practical instruction and advice in relation to risky or hazardous tasks in a secure setting through the use of AR and VR. At the University of North Dakota, for example, engineering students learn about heavy machinery operation using VR, lessening the likelihood of any mishaps or injury.

These five advantages highlight how AR and VR have the power to change the face of business education and give students a more productive and enjoyable educational experience.

Overcoming challenges and concerns

Of course, there are challenges and concerns associated with integrating VR and AR in business education. For instance, it is imperative that problems associated with costs and accessibility are resolved. It is also essential to guarantee data security and privacy in the online learning environment. Furthermore, training and upskilling educators to use AR and VR effectively in the classroom must be a central and continuous consideration.

Finding an ideal balance between traditional teaching techniques and technology-based instruction continues to be an issue. However, the potential advantages of AR and VR in business education continue to exceed the drawbacks as difficulties are addressed and lessened.

Certainly, the introduction of VR and AR into business education signals the beginning of a revolution in education. These technologies offer a range of potential advantages, including increased student motivation and engagement, better learning outcomes and the development of all-important soft skills. Real-world case studies, in particular, demonstrate the effective use of AR and VR in business education, and their potential influence. However, issues around price, usability, data security and teacher preparation all need to be addressed to maximise the opportunities these technologies present and bring business education into the cutting edge of a fascinating and inventive future.

Hemachandran K is an associate dean and director of the AI Research Centre at the School of Business, Woxsen University in Hyderabad, India

Raul Villamarin Rodriguez is vice-president at Woxsen University

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New Tech EMBA the product of partnership network in Italy

Business Impact: New Tech EMBA the product of partnership network in Italy

New Tech EMBA the product of partnership network in Italy

Business Impact: New Tech EMBA the product of partnership network in Italy
Business Impact: New Tech EMBA the product of partnership network in Italy

A new executive MBA (EMBA) focused on business and technology has been launched by Cuoa Business School, in partnership with Politecnico di Torino.

Teaching for the two-year programme is being delivered across two weekends a month and will encompass more than 500 hours of classroom time. Much of the course takes place at Politecnico di Torino’s Master’s and Continuing Education School, with certain activities held at Cuoa’s campus in Altavilla Vicentina.

“The collaboration between Cuoa and Politecnico di Torino is a virtuous example of collaboration between university and business school, but it also involves businesses,” explained Cuoa Business School president Federico Visentin. “An advisory board of around 20 representatives contributed to validating the contents of the project and will discuss any additions to be made.”

Course content currently covers data analytics, artificial intelligence, innovation and the space economy in addition to more conventional business master’s subjects, such as finance and project management.

“This project is truly ambitious because it combines the technological dimension, the core business of our university, with the managerial one,” said Politecnico di Torino rector Guido Saracco. “Technologies today not only rapidly change the world of work and people’s lives, but they can and must also be a reference for the choices that the managers of the future will be called on to make.”

The new EMBA is a product of an alliance initiative launched by Cuoa in 2019. The Cuoa University Network Business School currently fosters collaboration between Cuoa and 17 different institutions spread across Italy.

This article is adapted from one that originally appeared in Business Impact magazine (Issue 4 2023, volume 18)

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AI: educational strategies for success

Business Impact: AI: educational strategies for success

AI: educational strategies for success

Business Impact: AI: educational strategies for success
Business Impact: AI: educational strategies for success

ChatGPT and AI and their potential to change the world of work is dominating the news agenda. For many in higher education the focus has been on how to detect when students are using this new technology to ‘enhance’ their exam results, or even cheat. In a world where machines can find most answers, those answers will only be as good as the humans inputting information – so it is imperative that future employees are well trained in asking questions and evaluating the responses. 

The average time a skill stays relevant used to be more than 10 years. In 2017, this had reduced to five and it declined to four by 2022. Soon skills will be relevant for less time than it takes to complete a degree. The combination of accelerated change and advancements in AI means that the skills required in the future will differ considerably. For example, organisations may assess candidates solely on their ability to perform in a role, rather than their credentials and prior experience.

AI cannot carry out high-level tasks but it can perform as a collaborator, something that can be leveraged to delegate lower-level tasks and free up time for humans to concentrate on developing those skills they need to thrive. It is up to educators to show students the way by incorporating AI into the natural flow of work. 

Here are five ways in which educators can support students in leveraging this technology.

Emphasise the importance of AI adaptability in classrooms

It is up to educators to emphasise that young people will not only have to live with AI, but also create an ecosystem using it to build vital skills. A growth mindset willing to take risks, fail and think of innovative solutions and ideas is a significant skill future leaders will need to embody. While technical skills are important, the significance of soft skills such as leadership, social influence, empathy and active listening cannot be neglected. As stated by the World Economic Forum, these skills rank among the top 10 in the category of self-efficacy and collaboration.

Developing skills in AI is not just about technological aspects. It is also concerned with examining the output generated by AI tools and building a mindset to leverage this. Conceptual understanding of AI will empower students to not only use it productively, but also evaluate and critique output professionally. Engaging students in discussions regarding the societal impact of AI, encompassing issues such as biases, privacy and ethics, facilitates the development of their ability to voice their opinions and provide constructive feedback.

Students can hone their ability to evaluate and develop professional scepticism skills by broadening their knowledge beyond the learning of technical abilities, such as understanding algorithms and programming languages. They can then hopefully contribute to the field of AI with wisdom and be leaders who necessitate a holistic approach that considers the broader implications and consequences of using AI tools. This allows them to recognise the limitations and potential biases inherent in AI algorithms, enabling them to contribute to the refinement of AI systems.

Integrating AI into classrooms can involve project‑based learning that revolves around students exploring real-world challenges, using AI to decipher problems and developing innovative solutions exploring the output generated by AI. Interdisciplinary team projects can promote skills such as critical thinking, problem-solving, data analysis and teamwork. These projects expose students to AI’s transformative potential and prepare them for AI-driven careers.

Give students hands-on experience to develop skills

By understanding the potential of AI and its impact on various industries, institutions can ensure that students are equipped to navigate an AI-driven world. This includes staying updated on AI applications in specialisations chosen by the student body.

According to the World Economic Forum, nearly one in four jobs are set to change over the next five years. The factors driving this trend include AI, digitisation, the green energy transition and supply chain reshoring. As the job market is set for a new era of turbulence, resulting in a decline in clerical work, employment growth will shift to areas such as analytics, management technology and cybersecurity, while the fastest-growing job roles will be driven by technology, digitisation and sustainability. On one hand, the fastest-declining roles are clerical but, on the other, analytical and creative thinking will remain the most important skills for workers until at least 2025.

Students must also consider this changing landscape and develop their digital cognitive thinking ability. Intelligent tutoring systems, such as ALEKS (for mathematics) can particularly benefit students, as the system uses knowledge tracing and machine learning to adjust the level of difficulty and provide guidance according to the student’s strengths and weaknesses.

Building impactful and influential global citizens is the major task of the ‘New Age’ educational institutions. Novel opportunities are being curated for people who are capable of explaining how the engineering and design of new technologies affect the political, economic, social and cultural sectors. Sharing insights about recent developments in the industry and implementing measures to cope with the dynamism of these mini-industrial revolutions can help students adapt within this turbulence.

Collaborate with industry for experiential learning

ELP, or experiential learning programmes, can enable students to apply theoretical knowledge of technology and AI to practical business scenarios. Within ELP, students gain the opportunity to collaborate closely with real companies, prepare consulting proposals, research, report and make recommendations to the client. The process is guided by industry experts and faculty advisors and the end result is an innovative culture that yields unparalleled insights into the global economy, assessed by first-hand experience.

Crucially, this hands-on approach encourages students to develop critical-thinking, problem‑solving and team-building skills while they work on real‑world business challenges. Tools such as Forage and InsideSherpa can assist students by generating fast‑paced virtual internships, which allow them to gain practical skills and industry experience.

Experiential learning can be extended beyond virtual internships where institutions can directly connect with senior alumni and industry professionals with expertise in technology and AI for mentorship. Mentors possess valuable experience in their fields, which helps the mentees develop a deeper understanding of the market with real experience-sharing.

Furthermore, institutions can also help by setting up a founder’s lab on campus, which allows students to immerse themselves in entrepreneurial endeavours, fostering innovation and business acumen. Building clubs and organising events related to the field of AI creates platforms for students to network, collaborate and apply their knowledge in practical contexts.

Experiential learning often generates vast amounts of data. The integration of AI in ELPs can help students and institutions analyse this data to identify patterns, trends and insights, which helps them gain a deeper understanding of the learning outcomes. AI algorithms can provide valuable feedback based on data analysis, enabling students to reflect on their experiences and make informed decisions for future endeavours.

The key objective of integrating AI with ELP is to enhance students’ learning experience by exposing them to real-life, fast-paced, agile scenarios that require them to apply their skills in a practical setting. This allows them to gain a hands-on understanding of the world of work and core business concepts that they can incorporate in the competitive workforce.

Include AI development in programme curricula

It is critical to stay abreast of AI trends to facilitate learning and assessments, as this allows for the curriculum to be reviewed and adjusted in order to encourage the fundamental integration of AI and the transformation of learning methodologies.

The learning-by-doing approach, combined with awareness of trends regarding the potential of AI to support learning, will aid institutions in evaluating and modifying curricula. This will help promote and foster adoption of creative AI solutions in a course’s teaching, learning and assessment, in areas where the benefits of using AI clearly outweigh the risks. AI solutions can facilitate well-defined learning tasks in different subject areas and support the development of further tools for interdisciplinary skills and competencies. 

Further advanced uses of tech-enabled tools such as virtual reality (VR) and augmented reality (AR) within classrooms will enable students’ exposure to technology, while getting them accustomed to using these tech tools. Examples of VR and AR presently used in education include Blippar, Eon Reality, Google for Education, NeoBear and VRMonkey. 

While an integration of AI in the curriculum can benefit learning and assessment methodologies, it is essential that the trainer’s role is also regularly reviewed and redesigned if necessary, making sure trainers have competencies such as analytical thinking and innovation, instructional design and technological literacy, learning strategies and change management, ethical and moral reasoning and data interpretation.

Faculty must also regularly undergo training, including professional accreditations such as Advance HE. Developing appropriate capacity-building programmes – training and development such as documenting pedagogy through teaching cases – will prepare faculty to work in AI-rich settings. 

Use AI tools in career development programmes

Just as AI is transforming the job market, universities and colleges are beginning to harness its power to provide students with more effective career services. As the workplace evolves, it’s increasingly important for students to have access to the tools and resources they need to navigate the job market successfully. By incorporating AI into career development programmes, it is easier to analyse data, predict trends and offer personalised recommendations. AI-powered career services can help students find the perfect job match.

To optimise their CV, tools such as resume analysis can be used. AI tools such as Big Interview can take recorded interviews, assessing various features of the face and body language along with pitch and tone to help students finesse their screen presence skills. Students can use case study simulations to analyse the situation and choose a course of action based on the possibilities presented. AI can then identify the optimal scenario and share the results.

Platforms for skill assessments identifying competitive strengths, personality traits and opportunities for development can also set out the best set of roles for an applicant based on their skills, talents and qualifications by examining an array of job roles. Through this, students gain valuable insights into the job market and learn how to promote themselves.

AI-powered tools can analyse vast amounts of student data, including performance, learning preferences and progress, to provide adaptive learning experiences. In order to forecast future job prospects, predictive analysis tools can examine vast amounts of labour market data, including job postings, hiring trends and economic indicators. Lifelong learning tools can also suggest upskilling courses, modules and certificates by studying a candidate’s profile, capabilities and experience.

By harnessing machine-learning algorithms, educators can customise content delivery, adapt teaching strategies and offer personalised feedback to students. Such an approach can cater to individual learning needs, facilitate deeper understanding and improve overall learning and employment outcomes.

Summary: embracing AI to face an ever‑changing job world

From technical to soft skills, with AI becoming so prevalent, it is critical that students and faculty are open to its potential and willing to embrace its power. It’s not just about learning new skills; it’s also about cultivating a progressive mindset, which involves perceiving obstacles as opportunities for growth and lifelong learning. Students who adopt this perspective are better ready to overcome challenges and adapt to new conditions – critical in an ever-changing job world.

This is the future where leaders are expected to take bold transformational decisions for growth, adaptability and willingness, to have a human outlook while collaborating with artificial intelligence. In fact, the World Economic Forum recently highlighted this ‘skills-first approach’, noting that the ability to flexibly and efficiently learn and apply knowledge across situations to bridge the demand-supply gap in industry will prevail, despite many uncertainties. Moreover, learning will extend beyond traditional upskilling programmes and encompass ‘everyday learning’ in unconventional ways. This approach will nurture curiosity, encourage questioning and foster aspirations, all while being immersed in the learning process.

The time to re-engineer our way of engaging and executing tasks is now, as we ride the wave of AI development; think of this technology as your personal brainstorming colleague. Through embracing the age of AI, higher education institutions can support students to leverage the endless possibilities. Of course ‘evergreen’ skills such as integrity, transparency, communication, agility, risk management, innovation and being a good listener, will continue to be important in the future. But the biggest winner will be the ability to lead through disruptive dynamics with courage, empathy and innovative thinking.

Uma Ashridge Portrait 385 Y

Uma Gunasilan (pictured, left) is the associate dean of research and the chair of AI at Hult International Business School

Nikhil Soi is a career development advisor at Hult International Business School

Nikhil Soi

How will generative AI impact higher education?

Business Impact: How will generative AI impact higher education?

How will generative AI impact higher education?

Business Impact: How will generative AI impact higher education?
Business Impact: How will generative AI impact higher education?

The OECD’s initial prediction that around 1.1 billion jobs will undergo significant transformation due to artificial intelligence (AI) over the next decade now seems quite cautious in light of the rapid advancements in technology. Advanced AI systems, such as GPT-4 and Midjourney, have broadened the horizons of what AI can achieve. They can generate diverse content, understand complex scientific concepts and have the potential to reshape industries, such as medicine and entertainment.

It’s clear that the scope of AI’s capabilities has surpassed earlier expectations, prompting a re-evaluation of skills and professions. This changing landscape emphasises the importance of adapting higher education to equip individuals for this AI-driven world.

In this, the concept of ‘humanics’ put forward by the World Economic Forum’s Education 4.0 initiative is critical – fostering skills that are resistant to automation, such as creativity, interpersonal awareness and civic responsibility, will be invaluable in the changing job landscape.  

Yet, underscoring the ethical dimensions of AI’s growth is an open letter from the Future of Life Institute that calls for restraint in training AI systems beyond GPT-4’s capabilities. Endorsements of this letter from influential figures, such as Elon Musk and Steve Wozniak, demonstrate the concern for responsible AI development.

AI’s expansion

In spite of such challenges, AI’s power is expected to expand, reshaping industries and potentially redefining the nature of work itself. Generative AI’s transformative potential spans diverse fields and will make its presence keenly felt in education. Content creation is a prime example, as it offers industries that include media and marketing a tool to generate written materials, leveraging models such as GPT-3 to produce news articles and other forms of written content. Generative AI also has the power to aid researchers in crafting academic research papers and literature reviews, streamlining information synthesis and laying the groundwork for further refinement.

In higher education, generative AI is already reshaping simulations and virtual laboratories. Virtual patient simulators in healthcare, for example, simulate clinical scenarios and enable medical students to refine their skills in a risk-free environment. In engineering, digital prototypes and simulations replicate real-world situations, facilitating efficient product testing and development. Intelligent tutoring  technologies are also evolving, with generative AI helping platforms, such as Carnegie Learning, to deliver personalised guidance based on individual student performance, thus enriching the learning journey.

Why higher education must adapt

As AI continues to disrupt industries and redefine job roles, it’s essential for universities to step up and adapt their approach to education, ensuring that students are equipped not just with technical skills, but also with the cognitive and social skills that can’t be easily automated. Blending theoretical knowledge with practical experience through experiential learning programmes is one proactive strategy that can help business schools prepare students for an AI-driven future. Such programmes offer students the chance to establish meaningful connections with their environment and peers, giving them a competitive edge over automation. By immersing students in AI-driven workplaces, they can gain a deep understanding of industry fundamentals, even if AI begins to narrow traditional entry paths.

Experiential learning serves as a valuable alternative route, catering to a changing landscape. The impact of this shift extends far beyond the classroom. It reshapes apprenticeships, corporate training and educational technologies, fundamentally altering the existing educational system. It calls for universities to pivot their focus towards lifelong learning, recognising that the dynamic nature of AI and technology requires continuous adaptation.

In addition, this transformation aligns with the evolving needs of non-traditional learners by bringing the focus on to tailored programmes that cater to their evolving professional requirements. The synergy between experiential learning and generative AI showcases the dynamic potential of education in preparing individuals for a rapidly changing landscape of work and technology.

How AI can improve higher education

Generative AI’s influence in education spans a wide range of areas. Platforms such as Duolingo use generative AI to create language lessons and offer immediate feedback. Writing assistance systems, such as Grammarly, use generative AI to recommend ways to enhance your grammar, style and ability to spot plagiarism. Existing applications of the technology also extend to data analysis and visualisation, where tools like Tableau use generative AI to suggest efficient ways to present complex datasets in order to facilitate interpretation.  

These examples highlight the varied functions that generative AI may serve to improve education. It has the potential to transform higher education in a number of ways. One significant application is content creation, which enables generative AI models to create excellent instructional materials. This might entail writing well-organised research papers, perceptive essays and thorough textbooks and would allow educators and researchers to focus on other important facets of their job while also saving them significant time.

Generative AI also presents opportunities for individualised learning. The algorithms behind the technology can produce custom content that caters to the distinct requirements and preferences of each student by examining individual learning patterns. This could entail creating tests tailored to each student’s learning preferences, interactive activities, or even life-like simulations. Additionally, generative AI models acting as virtual teaching assistants accompany students in real-time by providing prompt responses, precise justifications and customised coaching. Bring with it a guarantee of prompt support and clarification, this type of personalised feedback stands to improve the learning process considerably. 

The significance of generative AI is further expanded by its potential applications in language learning and translation. To help learners master new languages, it can produce language drills, conversations and pronunciation manuals. Additionally, it can make translation work easier while encouraging a greater grasp of other languages and efficient interlinguistic communication. Similarly, it can speed up research and data analysis across a variety of academic domains, by developing hypotheses, navigating enormous datasets, and modelling difficult scenarios. In the arts, generative AI offers ways to ignite innovation and stimulate the birth of new artistic movements, musical compositions and architectural ideas. In this light, it becomes clear that generative AI has the potential to revolutionise education by precipitating and facilitating a re-evaluation of how humans discover, create and learn in a variety of contexts.

Rajat Gera Business Impact

Rajat Gera is director of research at the School of Business, Woxsen University.
Gera has co-authored more than 50 international and national publications, as well as three edited books and case studies published by Western University’s Ivey Business School and London Business School. He holds a PhD in management from University School of Management Studies, Guru Gobind Singh Indraprastha University, New Delhi

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Digital transformation: What business schools should teach

Business Impact - Digital transformation: What business schools should teach

Digital transformation: What business schools should teach

Business Impact - Digital transformation: What business schools should teach
Business Impact - Digital transformation: What business schools should teach

Business schools should teach students about digital transformation in the same way companies see and do digital transformation. For example, most ‘digital transformation’ projects are not ‘transformative’. They don’t disrupt business processes or whole business models. Instead, they tend to be ‘incremental’ or just as often part of planned technology ‘modernisation’ initiatives. These kinds of projects are safer, less expensive and ‘politically’ protective of executive reputations, which is perhaps why the vast majority of digital transformation (DT) projects go down this line of focus.

Real DT projects that are truly transformative have targets of replacing or automating business processes, or replacing or automating whole business models. These goals are riskier, more expensive and politically dangerous than incremental/modernisation ones. Impact and risk are brothers and sisters: incremental/modernisation projects are easily less impactful than disruptive ones. Companies must decide what and how they want to ‘transform’, acknowledging the likely return on their DT investments. But eventually, because of the trajectories of technology and business, they will have to pursue more disruptive transformation and leave incremental transformation to operational technologists. The difference between incremental/modernisation DT is small and in fact not that different from ‘business as usual’. Will incremental/modernisation DT keep companies competitive? Will they enable profitable growth? Are they responsive to the competition? Can companies respond slowly to market trends believing they always have time to pivot to more disruptive behaviour? Or should they pivot to disruptive transformation? These are some of the questions that should be explored in business school.

Five digital transformation myths

Myth #1 – some companies can skip DT: It’s clear that every company must incrementally change the way it does business and modernise its ageing systems. Companies that refuse to change at all will find themselves at a competitive disadvantage. So, yes, every company needs to digitally transform, but we should note that refusals to change will likely be listed by the business coroner as the most likely cause of death.

Myth #2 – DT must leverage emerging or disruptive technologies: Incremental and modernisation-focused DT often uses conventional, existing digital technology. There’s often no need to adopt emerging technology to affect incremental changes or modernisation projects. Incremental/modernisation DT can stick with tried-and-true technologies. But disruptive transformation almost always leverages emerging technologies.

Myth #3 – profitable companies are more likely to launch digital transformation projects: The assumption that market leaders are the most innovative is usually false. Companies doing well believe that doing well is the result of repetitive processes and an unassailable business model. They do not believe their path to profitability should be disrupted.

Myth #4 – companies need to disrupt their industry before someone else does: Market leaders do not usually sense disruptive competition, especially from new entrants. So, no, market leaders are not obsessed with vulnerability. Instead, they feel strong and powerful, even invulnerable to disruptors that impact whole industries, such as Airbnb (hospitality), Uber and Lyft (transportation), Amazon (retail), SelectQuote (insurance) and Netflix (entertainment), among others that have reinvented a broad range of vertical industries.

Myth #5 – executives are hungry for DT: They’re not – unless their companies (and therefore themselves) are threatened by falling revenues and serious competition. But that doesn’t stop executives from talking endlessly about their digital transformation projects and goals.

Benefits of using the case study method

Case study analysis is a business school staple. Teaching students about the different types and myths of DT and then presenting them with some specific case studies would enable a good understanding of the range and impact of DT projects. Business schools might consider offering some dedicated classes or programmes that are organised in this way. They could also assign cases to students, or groups of students, to spark debate on the opportunities and risks around DT. Such cases should breathe life into classes that are managed by professors of practice. However, it’s integral that the process is led by identifying the types of DT projects companies undertake and the myths that surround them. DT is not abstract, theoretical or hypothetical. It’s in the trenches and should be taught that way.

Stephen J Andriole is professor of business technology at Villanova School of Business in the US and author of The Digital Playbook (FT Publishing International, 2023).

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How technology is taking business education beyond borders

Business Impact: How technology is taking business education beyond borders

How technology is taking business education beyond borders

Business Impact: How technology is taking business education beyond borders
Business Impact: How technology is taking business education beyond borders

Together with online learning platform Kortext, AMBA & BGA recently brought together a group of senior leaders from European business schools to discuss the challenges and opportunities associated with borderless teaching and learning.

The discussion centred around the transformation that the Covid pandemic has wrought. As well as geographical borders, the term ‘borderless’ also refers to time; with the switch to online, business schools are no longer facing time zone limitations as technology allows students to complete their programmes at their own pace, wherever they may be in the world.

In order to offer this borderless education, business schools will need to provide an intuitive and integrated product that is both fit for purpose and personalised towards the needs of students. This is a key area of investment for business schools, with a recent AMBA & BGA survey revealing that 82 per cent of business school leaders are planning to invest further in digital teaching methods over the coming two years.

How is your business school going to take advantage of borderless education and what strategies are you putting in place to become borderless?

Peter Konhäusner, professor of digital entrepreneurship, Gisma Business School, Germany

“The interesting thing is that for us borderless education started even before the pandemic because we have a hyflex model here at Gisma Business School – you can always join in a hybrid way and we are able to offer students maximum flexibility.

“Students can join from around the globe whenever they want and can work through all the programme topics whenever they want. This is our take on reaching the maximum audience in terms of students. 

“On the other hand, it’s also about offering diversity in different stages – this is about synchronous, as well as asynchronous, content. 

“If students are having problems with their visa for coming to Germany for example, they can learn from anywhere in the world and watch recordings of sessions when they have time.”

Steven De Haes, dean & professor of information systems management, Antwerp Management School, Belgium

“In our case, embracing digital capabilities towards amplifying impactful learning journeys was already in the core of our strategy for many years. Of course, the Covid pandemic has accelerated this journey.

“We are further enriching our product portfolio itself, so we are broadening our reach towards having programmes that are mainly organised in interactive campus learning experiences, but at the same time we are also unfolding a fully online portfolio in a digital campus. Programmes in this digital campus are delivered either synchronously or asynchronously, so in that way we can reach a global audience.

“We are accelerating in hybrid learning approaches, blending the optimal mix for an impactful learning experience of synchronous and asynchronous and online and on-campus experiences. We have also had some visa issues and problems with students arriving on time at the campus, so they have the opportunity to attend classes in a hyflex online formula before they come to Europe. 

“As a result of having digital-enabled learning journeys, we are capturing more high-quality data on the learning journey itself and the learner experience and impact. We can now accommodate the learning journeys and impact on students in a much better way than previously because we are capturing much more data.”

Mark Dawson, director of digital education and senior teaching fellow, Lancaster University Management School, UK 

“Prior to the pandemic, the university already had a strong online provision but Covid-19 has enhanced the capability of the university – and our school in particular – so it is now more flexible when delivering blended or hybrid teaching and can accommodate a number of different pedagogical and delivery models.  

“I think we’re still in a period of flux; the pandemic is not over completely and we are part of a sector trying to find the right balance between online and face to face.  

“We’re seeing different demands for this at different levels of provision. Undergraduates are still largely learning in a face-to-face environment, but postgraduates and our executive or post-experience provision is highly blended and online.  

“I think there’s certainly an appetite here for further investment – there are a lot of opportunities. We’re exploring all manner of things in terms of emerging technologies, such as augmented and virtual reality.  

“In a way, the pandemic accelerated that. The appetite is there to grow this area of provision – certainly when it comes to blended. Blended learning has been around for decades, it’s just that the ratio of the blend has started to shift post-Covid towards a better balance between online and face to face. The ability to deliver that has grown, developed and matured to a certain extent over the past couple of years.”

Diana Limburg, MBA director, Oxford Brookes University Business School, UK

“This is all demand-driven. At Oxford Brookes, the Global MBA has been an online programme since the early 2000s and a blended programme since around 2016.

“The reason why we are a blended programme is that we have students all over the globe and they are all working. Therefore, it is demand-driven in terms of how we can make an MBA work for this type of student; then it becomes horses for courses because different types of students will need different pedagogies and different delivery modes.

“That’s the basis of how you make decisions on where to invest and focus. For us, we need a mixture of asynchronous delivery to make it flexible for students, but also synchronous delivery so they can have that real-time conversation and feel more strongly engaged.”

How have you adapted your strategies to attracting and retaining a more international cohort of students?

Aldis Sigurdardottir, MBA director, Reykjavik University School of Business, Iceland

“We don’t have that many international students, it is more of a local focus. We have about 85 per cent of our students who are local, they are here for networking – that’s a big draw for them and creates a big demand. That is usually the reason they are coming to the programme because they really want the face‑to‑face interaction.

“We have actually taken that direction – we don’t have that many international students at the moment. Those who are international, they live here and they work here – it’s more or less always in‑house. Because everyone lives locally, we have decided not to offer any online streaming of classes next year.”

Mark Dawson, director of digital education and senior teaching fellow, Lancaster University Management School, UK

“I think the challenge here is to embrace the potential of digital education in a post-Covid world, while still retaining that intimacy of face-to-face teaching. I’m not sure that the technologies are there for that yet, but that is hopefully where we are heading. 

“The challenge is to adapt in a way that maintains the aspiration of a borderless education, while trying to steer our technological systems away from the impersonal and towards a more intimate, challenging space for education to happen.”

Yasmina Kashouh, head of international programmes and academics at College de Paris International, France

“Essentially, we did something different, mainly due to the fact we have a large portfolio of schools around the world and we support portfolio enlargement by adding programmes to the local offer of our international partners.

“Our strategy was very clear: we move the programme – we don’t move the campus and we don’t move the students. So we worked with our partners to combine local operations with our strategy. Within these programmes, we use traditional on‑the-ground sessions with the online sessions to support our reach locally.

“We had a lot of challenges when students had to come to study internationally in France. We had the rise of the cost of transportation, visa issues, political instability, Covid – we also had issues with international forms of finance, something that complicated the payments from our students.

“The strategy we use is to move the operation itself – we produce our programme locally and then we can blend together online and on the ground.”

Steven De Haes, dean & professor of information systems management, Antwerp Management School, Belgium

“At Antwerp Management School, our MBA-level programmes are primarily geared towards intensive face-to-face interactive learning experiences, supported by a hybrid mix of online synchronous and asynchronous learning formats. I think ‘impactful’ is the key word here. 

“The whole conversation that we are currently having should not be about the technology itself, but rather about how we can amplify the impact of the learning experience towards the student – and of course – technology is a very powerful instrument in terms of amplifying that impact. 

“Along with amplifying the learning impact, technology opens opportunities to more easily reach the global market. At this moment in time, we have more than 44 different nationalities on our full-time master’s programme, so being and thinking global is already, and has always been, in our DNA. We continue to fully focus and invest in global outreach and impact.

“To give you a very typical example, over the past two years we have developed two professional digital teaching studios that allow faculty to engage in a very interactive way when we have students studying abroad, so
they are not on campus. With this professional digital studio, you can have faculty members teach as if the class were on campus. This optimises the experience for both the faculty member and for the learners, leading to higher impact with a global reach.

“In terms of reaching an international audience, we are also currently building smaller micro‑credential-type lifelong learning journeys, both synchronous and asynchronous self-paced modules, in order to reach new global audiences we could not reach before.”

Diana Limburg, MBA director, Oxford Brookes University Business School, UK

“We had online capabilities prior to Covid, so it’s not about reaching a new market, it is about being able to engage with people in a new way.

“We were doing successful online teaching before all of this happened. You can imagine trying to do this before everyone knew what Zoom was – it makes it a very different challenge.

“For us, it became easier, as suddenly all these technologies were accessible and not just for people based in the UK, but for people all over the world.

“Before Covid, there were platforms available but they were clunky, expensive and not easily accessible. Now, with these platforms, you have a global audience who can use the technology, as it’s even been embedded into their personal lives. People do yoga and have social engagements online, so they have much more of a foundation to use that technology in an integrated way in teaching and learning.

“It is absolutely about enhancing the experience, but it’s also about enhancing the ability to learn. They were learning what they needed to learn before, but it’s easier now to have more engagement, to have more interaction and to have more social aspects through that interaction. I think that’s important and it’s much more straightforward online now than it was previously.”

Peter Konhäusner, professor of digital entrepreneurship, Gisma Business School, Germany

“Another big topic we can touch on when thinking about going online – which is also a challenge as well as an opportunity – is diversity.

“Right now at Gisma, we have in our MBA programme an average of nine years’ experience in the field, which is great. But it means that you have to find a common, level playing field to pick them up and carry them forward. All the students are coming from diverse backgrounds, ethnicities, origins and so on, which is fantastic for networking as many of the students want to have global opportunities after their programme to work and travel.

“But there is also a challenge associated with managing this diversity and this different level of knowledge. It’s great to let people talk about their own experiences – because that is such rich content. I think this is something that is really enhanced by having a global audience, the richness of cultural and business backgrounds.”

What is your business school’s unique selling point? How do you stand out in a truly global education market?

Aldis Sigurdardottir, MBA director, Reykjavik University School of Business, Iceland

“We are looking into sustainability and the use of sustainable energy – that is our niche. That is how we differentiate ourselves and use our specialities and knowledge, for example, in the fisheries industry. It is certainly very niche, but that’s where our natural resources and knowledge are.

“We have a dilemma though, because our students are mainly from Iceland and I think this would be very interesting for an international student, but not so much for people from Iceland.

“That means we are reluctant to go all the way into this speciality because of that. Our students are really looking for a good international programme that is compatible globally.”

Yasmina Kashouh, head of international programmes and academics at College de Paris International, France

“Going back to the business schools’ USPs and how they became more crucial, the differentiation will come from the ability and the capacity of the school to match the jobs that are needed.

“The closer business schools are to be able to train people to find jobs, the better. That is why the traditional knowledge, although it’s important, is not enough.

“The capacity to generate self-determined, reliable, proactive learners who are able to learn, unlearn and relearn – that will remain the main role of a business school.”

Roundtable attendees

Chair
Colette Doyle, head of editorial, AMBA & BGA

Panellists
Mark Dawson, director of digital education and senior teaching fellow, Lancaster University Management School, UK
Steven De Haes, dean & professor of information systems management, Antwerp Management School, Belgium
Yasmina Kashouh, head of international programmes and academics College de Paris International, France
Peter Konhäusner, professor of digital entrepreneurship, Gisma Business School, Germany
Diana Limburg, MBA director, Oxford Brookes University Business School, UK
Aldis Sigurdardottir, MBA director, Reykjavik University School of Business, Iceland

Kortext is a digital content and student experience expert, leading the way for digitally enhanced teaching and learning in the global education community.

This article originally appeared in the print edition (Issue 2 2023) of Business Impact, magazine of the Business Graduates Association (BGA).

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How VR can help students step beyond the classroom

Business Impact: How VR can help students step beyond the classroom

How VR can help students step beyond the classroom

Business Impact: How VR can help students step beyond the classroom
Business Impact: How VR can help students step beyond the classroom

Since the third industrial revolution kicked off in earnest in the late 1900s, the world has seen a dizzying array of new technologies become part of our lives: from harnessing nuclear power to the invention of the ethernet and the creation of wireless devices, web pages, social media platforms, mobile phones, money services like Kenya’s M-Pesa and the Internet of Things. And things are not slowing down.

In the current fourth industrial revolution, technologies like virtual reality (VR) and artificial intelligence (AI) are disrupting how we learn, develop, connect and even empathise.

Dubbed theempathy machine’ of the tech world, VR has been shown to encourage empathetic behaviour by encapsulating the qualities of presence and embodiment. Project SHELL, an immersive 15-minute VR simulation designed to garner support for the conservation of the loggerhead turtle was designed by a professor from the University of Oregon in the US and is a case in point. 

In the simulation, students wearing Meta Quest 2 VR headsets immerse themselves in the real world of the loggerhead turtle. They effectively become the turtles – arms morph into flippers and backs curve into shells as they embark on a journey from hatchlings to adults, experiencing the hazards confronted by real turtles in their natural habitat. 

Daniel Pimentel from the University of Oregon, one of the study’s co-authors, said the students’ feelings didn’t fade once the headsets came off. “From a sensory perspective, the dangers [they] faced while embodying the turtle threatened [them],” he said. 

The potential to accelerate learning through VR

In the world of learning, the possibilities presented by these kinds of experiences are deeply exciting. Already, it is becoming clear that new approaches must be harnessed to develop relevant, empathetic and socially minded leaders who are equipped to understand and tackle the complex environmental, social and governance (ESG) issues of our time.

It’s hardly surprising, therefore, that forward-thinking business schools are already starting to embrace VR tools to bring practical insights alive and deliver content more innovatively as they vie to attract students.

The massive potential of these approaches have long been recognised. In 2021, professional services firm PwC released findings that highlighted the value of using VR tools to support soft skills training, and as a way of helping businesses to upskill employees faster and more cost-effectively. The study showed that using VR enabled learners to absorb information four times faster than they could in the classroom alone and with four times the focus compared to their e-learning peers. Perhaps more impressive is that VR learners were 275% more confident when applying newly acquired skills than they were before the learning intervention and 3.75 times more “emotionally connected to content than classroom learners”.

While some business schools, notably in the US and Europe, had already started exploring VR teaching methods before 2020, the Covid-19 pandemic has undoubtedly accelerated investment into online and “virtual” learning. However, it is also becoming very clear that, as Dot Powell, Warwick Business School’s director of teaching and learning enhancement, said in a recent interview with the Financial Times, learning approaches that simply require lecturers to talk over a slide presentation “won’t be acceptable for much longer”. The appetite for authentic engagement with fellow students and course content continues to grow among students of higher education institutions. They want interactive and personalised learning and they want it now. VR gives us the power to give it to them.

Increasing access to education is also key

There is another reason that VR has significant potential, especially for poorer institutions in more remote parts of the world – it could help us to expand access to quality learning experiences.

At Henley Business School Africa (Henley Africa) we started experimenting with VR in 2019 as a solution to the limitations facing students from different countries in Africa when it comes to attending international leadership immersion programmes. There is ample evidence that face-to-face immersions are inherently valuable to students, but the high cost of participation including flights, time constraints (limited close-up encounters between participants) and restricted student numbers (only 20-30 students per immersion) could not be ignored. It is a luxury few can afford.

Of course, a significant stumbling block in a country with high levels of inequality, like South Africa, is the cost of the technology itself, which makes it impractical for all students to purchase their own devices. In confirmation of its support for the initiative, Henley Africa has committed to investing in the technology and making headsets available for individual use as required. 

Where to from here?

As the body of research into VR as a learning tool grows and more practical business school case studies emerge, the value of incorporating innovative digital platforms and technologies into the business school facilitation mix will become increasingly evident. 

As our experience at Henley Africa shows, a successful shift towards VR cannot be achieved without support across the business school. This is an evolving journey and as more schools share their VR experiences and increasing number of concrete models are bound to emerge. 

VR – and the future technologies that will, no doubt, grow from this base – have the potential to revolutionise the business school learning model so that it is more experiential, innovative and personalised. Above all, it is my hope that they will radically increase access to priceless learning experiences that will help to build authentic and empathetic African leaders who are empowered to create transformative businesses across the continent.

Louise Claassen

Louise Claassen is an executive fellow of Henley Business School Africa, co-founder of ORBmersive, and author of the white paper, Virtual reality in business education.

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How assistive tech can boost accessibility and inclusivity in higher education

Business Impact: How assistive tech can boost accessibility and inclusivity in higher education

Assistive technology can enhance the student experience and help those working with new languages as well as levelling the playing field for those with disability or lack of access, says doctor and entrepreneur, Richard Purcell

‘Assistive technology’ is the term used to describe devices and tools used to increase, maintain, or improve the capabilities of people with disability. This covers everything from low-tech tools, like pencil grips, to more high-tech tools, like speech-to-text.  

That being said, assistive technology is not only useful for those with a disability. Assistive tech can also be an essential aid for people with neurodiverse traits that may affect working memory, concentration, and writing speed.

It can even be used by those who are learning an additional language, or as a productivity tool to enhance a student’s learning experience and educational performance. For example, there are more than 100 studies which say that adding captions (i.e., same-language written translations) to video improves viewers’ understanding of what they see. 

Why do we need assistive tech? 

Around one billion people currently need assistive products, and more than two billion people around the world are expected to need at least one assistive product by 2030, according to the World Health Organisation (WHO).

Up until now, the disabled population has been absent from discussions on education and the practices used to deliver education, resulting in a huge gap. Assistive technology helps to bridge that gap. It reduces the need for formal health and support services, long-term care and the work of caregivers, according to the WHO. Without assistive technology, people are often excluded, isolated, and locked into poverty, thereby increasing the impact of disease and disability on a person, their family, and society. 

For people without disability, technology makes things easier. For people with disabilities, technology makes things possible.’ (From a 1991 IBM training programme.) 

Diversity and inclusion 

Ultimately, assistive technology can be used to level the playing field in higher education, allowing all students, no matter their ability, background, or learning style to thrive and get the most from their educational experience.

It can enable students to take control of their own learning and gain independence in their education. While students with additional needs are often perceived to be at a disadvantage, assistive technology enables them to reach their full potential, thus aiding diversity and inclusion in university settings. 

The more diverse and inclusive environments such as universities, workplaces and governments are, the more society can be pushed towards thinking about issues that might otherwise be overlooked, such as accessibility. Diversity and inclusion drive innovation and create a better world for us all.

What kinds of assistive tech can be used? 

Innovation and progress within assistive tech is happening every day. Just this March, for the first time ever, a project led by the University of Tübingen in Germany has helped a person with motor neurone disease to express himself in full sentences using a new technology that can read his thoughts.

Assistive technologies currently include, but are not limited to, the following. However, please note that new assistive tech is being produced and improved all the time: 

  • Text-to-speech / Speech-to-text 
  • Adjustable monitor arms 
  • Reading pens 
  • Alternative keyboards 
  • Voice recognition 
  • Digital recorders 
  • iPads and tablets 
  • Visual aids, graphic and drawing tools 
  • Electronic spellcheckers 
  • Word prediction software 
  • Visual search engines 
  • Literacy specific software 
  • Educational software 
  • Electronic resources and books 

What are the barriers to assistive tech?  

Almost one billion children and adults with disabilities, and older people, are unable to access the assistive technology they need, according to a 2022 report from the WHO and UNICEF. 

There are a range of barriers to assistive tech in higher education including: 

  • Lack of appropriate staff training and support 
  • Negative staff attitudes 
  • Inadequate assessment and planning processes 
  • Insufficient funding 
  • Difficulties procuring and managing equipment 
  • Time constraints  

These barriers can’t all be overcome at once but acknowledging that they exist and making sure that conversations are being had and action is being taken will ensure we are making the correct steps towards providing assistive technology to those who need it most.  

In the UK, the Disabled Students’ Allowance (DSA) can sometimes be used to cover the study-related costs, such as the cost of assistive tech, you have because of a mental health problem, long-term illness or other disability.

Assistive technology can help to remove the barrier people face in their day-to-day lives. It levels the playing field and allows all students to have access to the same experiences and learning environments. It’s important to remember that all students benefit from a more inclusive environment, and we, as a wider society, all benefit from a more inclusive educational system.  

Richard Purcell is an NHS doctor and entrepreneur, working to develop innovative assistive technologies designed to promote and enable diversity and inclusion in education and the workplace. Richard has established and grown two successful technology companies, Medincle and CareScribe. 

Adaptation, repair, or a new opportunity?

Business Impact: Adaptation, repair, or a new opportunity?

How has Covid-19 changed Business Schools’ priorities? AMBA & BGA was joined by experts from technology company, Barco, and representatives from the business education community to explore what the future might look like for Business Schools and their students in the post-Covid digital economy. By Edward Jacques and David Woods-Hale

Digitalisation is deemed to be the most important concept in the running of a Business School over the next 10 years, with almost two-thirds of leaders (63%) believing it to be very important, according to AMBA & BGA Education Technology Research, in association with Barco. 

In fact, a whopping 83% of leaders think it is either ‘very likely’ or ‘fairly likely’ that the fundamentals of the MBA will change in the next 10 years, compared with 76% who were of this opinion in late 2019.  

The research also found that Business Schools are looking forward to a new era of education technology, having made a success of online learning provision in 2020 – and Business School leaders have shown their Schools to have been both pragmatic and agile in the face of 2020’s disruption.

The next steps for Business School leaders across the world is to move from crisis mode to further innovation, in order to develop and finesse their tech strategy as global economies start to move into recovery as vaccines reduce the impact of Covid-19. 

AMBA & BGA, in association with Barco, held a focus group with decision-makers from Business Schools across Europe to find out in more qualitative terms whether Business Schools have changed, updated, or tweaked their models because of the pandemic during the past year; what plans are afoot for the coming 12-18 months; how Schools are identifying new opportunities for the year ahead; and how they are driving digital transformation and skills development. 

AMBA & BGA was joined by experts from technology company Barco – as well as representatives from the business education community – to explore the challenges. During a lively discussion, panellists took stock of what had changed since the onset of the Covid-19 pandemic, what they have learned, and what the future might look like for Business Schools and their students in the digital economy. Here are some highlights from the conversation. 

Simone Hammer, Global Head of Marketing Teaching and Training, Barco

We worked with a couple of early-adopting Business Schools that tried out our virtual classroom when the pandemic started, and they were happy and deployed more and expanded what they had in place. 

Many [Business Schools] have used conferencing systems to get through the pandemic – but we all thought it would be over in a couple of months and we now know that this is not the case. These Schools had the option to expand because they had technology already in place. 

Lots of people needed to be educated in understanding the solutions that are out there that can really bring them an immersive and engaging experience. I would that, say since the end of last year, lots of Business Schools have come to understand that platforms such as Zoom or Teams cannot deliver the level of engagement and the learning outcomes that they would expect for their programmes – and specifically executive education. We also are working with the corporate community to deliver learning and development to employees, and we are observing the same trends in this arena.

So in light of this, what is the way into the future? What have we learned? I would personally like to go a little bit further, and ask what is the revolution now? What can we do to be more inclusive and reach out to more people [through technology]? How can we make it more engaging?  What about belonging? What are the priorities and how can we help Business Schools to be even better despite the pandemic?

Schools need to embrace horizontal learning and create connections. Technology must enhance the physical and digital learning experience. I believe hybrid working and learning will be the new norm. 

How do we prepare the students for life outside the university? Business leaders want people who have a certain experience. They want them to learn something but they also want them to be prepared for a future in their companies. 

Rebecca Loades, Director, Career Accelerator Programs, ESMT Berlin  

At ESMT, we have separated content creation and content delivery in blended and online learning. This allows us to share and swap content with other Schools more easily.

When designing for online, every single minute of the course is thought about in depth. We therefore have to be much more precise in our preparation than when we are offering a course in person. Having that control, and being able to apply that rigour, is the gift of an asynchronous environment. 

Each of our online courses has a defined manual about how it should be taught. This approach enables us to separate course development and course delivery so that students learn from faculty with superb domain knowledge but may engage with a different faculty member during their learning journey.

We have some 550 degree-seeking students and a relatively small faculty body, so we had to make sure that we are using them in a way that equips us to serve our population base now, and also creates a platform for the future. 

In the global online MBA, the advantage for students is that they’re going to be learning in – and from – a programme that has virtual collaboration at its heart.  This means students are using technology for learning, and are learning from technology.  The first module in the Global Online MBA focuses on managing in a connected world. It provides students with hands-on insights around how to work with, and within, virtual teams.

At our Business School, we have invested approximately €500,000 EUR to upgrade our auditoriums. We have microphones at every seat and cameras that focus on who is speaking. This helps us to create an engaging environment. We also assign what we call a ‘co-pilot’ to each of our faculty members. In pure online, the co-pilot manages the chat and the technology; in hybrid scenarios, the co-pilot is the bridge between the online and in-person attendees. By having someone focused specifically on students who are not physically present, we ensure their voices are heard. We want to remove any sense of physical separation, so that virtual participants are equal contributors to the classroom. 

In a hybrid session, all students are required to connect via Zoom, including those who are physically present. It has contributed to a richer classroom experience as students share observations, insights, and related resources through the chat function. This not only helps students who are shy or don’t have English as their first language, but also nudges students to share things they may not think are worth interrupting faculty for, and yet which will support learning.

Gunther Friedl, Dean, TUM School of Management

We are still offering a classroom experience. If students have time, then they can come here; if they don’t, they basically tell us they cannot travel. 

Some students would like remote access [to learning] and others say they want to have the social experience. We have to accommodate all these needs in the classroom and that is a challenge because it requires technology. 

We learned how to integrate students from abroad into the hybrid learning setting, but this was quite a journey because students need to understand everybody in the room, so you require the technology to make this possible. 

This demand has grown extremely quickly during the past 15 months. Before [the pandemic] we were able to say ‘no’ to such demands. This is now our offering, and I don’t think [saying ‘no’] will be possible in the future so this [hybrid] flexibility
will be required by all institutions moving forward. 

Mindsets [in Business Schools] need to change to draw on possibilities and flexibilities, but students themselves need to be flexible as this is the new normal. 

Hybrid extends to other areas. No one thought hybrid meetings and learning [would replace] physical meetings, but this format will be around in the future.

Céline Davesne, Associate Dean, NEOMA Business School

We are currently working on hybrid and online learning with new pedagogy and a task force – including students, faculty, and other stakeholders. 

We are looking at ways we can manage networking experiences, and social aspects for students. We do feel, at NEOMA, that our virtual campus will be able to answer all these elements. Our virtual campus is a campus just like the others at the School: it has a library, amphitheatres, and student clubs. Everything is there, so students just use their avatars within that campus. 

We strongly believe in it and the high satisfaction rate from students means we are able to meet [their expectations]. The students were able to discuss things together, play football together, they could attend concerts together, and so on. We managed to recreate a social environment via virtual reality. 

This is something we want to keep and even to extend and I want to apply all these innovations to our executive MBA cohorts in Iran or China, for example.The virtual campus will be the place where our students have common case studies, and they can work together from cross-cultural perspectives. This makes a difference from Zoom because we can have the whole cohort in one amphitheatre to start with and then they can all join online as they wake up [in their respective time zones] and go to different classes and work together. This means that time and space can be seen completely differently, and that is an added value that we want our MBA students to explore.  

MBA students can use the virtual campus when they want to work with participants from different continents, and this means they can truly experience technology. They don’t simply use [technology], they experience something that’s almost fixed physically and cognitively. When they go back to their companies, students can say that they have worked with people of various nationalities remotely and have used a different technology that might be of interest to their company or [a future employer] when they want to boost their career. This is something we really want to enable for them. 

We’re talking about the digital workplace, so we want to enable the transition between what students are experiencing at Business School during their MBA on the virtual campus, and the working environment. 

Terri Simpkin, Director, Executive MBA, Nottingham University Business School

We’ve found that it’s not just about replacing the physical on-campus experience because of the [Covid-19] crisis. We’ve seen that students who would – under normal circumstances – sit in the back of the room and would probably never engage at all; people who perhaps can’t get a word in because there are more assertive people in the room. Those people are having their voices heard.  

People who are introverted, who don’t feel comfortable, or people who don’t have English as a first language are making highly valuable and timely contributions to a much broader conversation. It comes back to the idea of this learning experience being co-created.  

Before Covid-19, there was no compelling, burning reason for us to move to a situation in which we were putting ourselves into a position – as educators – where we were replicating and amplifying the emerging managerial and leadership paradigms that we were seeing coming from industry. 

We want to produce graduates who can manage in crisis situations; we want graduates who are able to think more expansively; we want to be able to challenge the prevailing notions of what leadership actually looks like. You can do that much better when you’re immersed in a space where it is a moving feast. 

We can’t underestimate the value of providing that real-time, real-life experience, but the technology has to be there to support it. Now the technology is a platform that provides [Business Schools] with the tools to do this. The whole notion of how MBAs are actually put to our communities, not just the students but our communities more generally, has to be reimagined and this is a really good point in time to do that. 

Antonio Giangreco, Director of Graduate Programmes, IESEG

In terms of technology and what we can use, there is a very long path ahead, because during the Covid-19 pandemic, we had a considerably higher volume of requests for psychological counselling that we had pre-Covid. 

In our School, we have very small groups with classes of less than 30 participants, so interaction in the classroom is guaranteed. Of course, in any other classroom –with 300 students – being there physically or accessing the lectures remotely from home, does not make a lot of difference. But when you are in a small environment, your peers push you to participate, even if you are in front of a computer. 

The world will never be the same. Everything has become reachable from everywhere. I think that this will lead to more flexibility so that, in some companies, employees will not need to go into the office anymore. 

This means we need to have people who are able to train, be trained, and then work in this context. This is a very good – but very tough – challenge for us as educators.

Learning should be enabling and if we ask what the enablers of learning are, the answer would be this horizontal learning, connections, and networking.

As Business Schools, we have to ask ourselves whether we can build something that might not be able to completely substitute a classroom experience but can help students get more from online learning; in other words, we nee to replicate the connection to the business world using horizontal learning. 

We need to be able to deliver the connection and networking, as well as the social aspect of a Business School, in an online environment. 

Preben Schack, VP of Sales, Learning Experience Division, Barco

It’s exciting being part of this revolution in online learning. I have been part of many disruptions throughout my life in the media world and I see this as one of the next disruptions. I’m fascinated to find out how we can use technology to make our education even better. 

I don’t think that what we have experienced throughout the pandemic is at its end. I think it’s at its beginning. I can confirm that what we hear around the world is that executives love to use online platforms, but they are more discerning when choosing software and programmes. This might have to change as we move forward to meet the needs of different MBA students and their courses.  

The big question for me is how do we make that experience better and how do we use technology to connect? The experience of teaching needs to be engaging and immersive but also affordable. And for this to happen, a possible strategy could be for institutions to collaborate and share technologies and platforms. 

How can we give professors, teachers, and students an even better experience in the educational space?  That is what I’m passionate about.  

Moderator 
David Woods-Hale, Director of Marketing and Communications, AMBA & BGA

Panellists
Céline Davesne, Associate Dean, NEOMA Business School
Gunther Friedl, Dean, TUM School of Management
Antonio Giangreco, Director of Graduate Programmes, IESEG
Simone Hammer, Global Head of Marketing Teaching and Training, Barco
Rebecca Loades, Director, Career Accelerator Programs, ESMT Berlin  
Preben Schack, VP of Sales, Learning Experience Division, Barco
Terri Simpkin, Director, Executive MBA, Nottingham University Business School

This article is adapted from one which originally appeared in Ambition – the magazine of the Association of MBAs.

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