The Future of Education in an AI World

Posted on: August 30, 2023

We reached out to Dr Kumaran Rajaram, Ph.D., an author of Leading and Transforming Organisations: Navigating the Future on the topic of AI integration in Higher education. We shared with him the recent World Economic Forum: Future of Jobs Report 2023 and discussed some of the highlights from the report, here are some of his opinions: 

1. The World Economic Forum Future of Jobs Report 2023 predicts that due to a combination of macro trends and technology adoption, over the next five years jobs in the Education Industry are expected to grow by 10%, leading to an additional 3 million jobs globally for Vocational Education and Higher Education teachers. How do you envision technology, such as generative AI, being integrated into tertiary teaching? And what impact do you think this will have on educators? 

o What does a sustainable learning-first approach with AI look like?
Primarily, it requires a major mindset shift and how educators view learning fundamentally. With the intervention of AI, the design of how learning happens requires a radical transformation. The focus should be more on the learning process instead of merely the learning outcomes. AI can provide the mere information required so the process of learning should be re-designed to build to make more meaningful critical thoughts, the questions of “why” and “how” becomes even more essential than before, so that there is space for learners to think critically and critique to build on and re-shape the information to a higher level of depth and analysis. Rightfully in the scholarly book titled ‘Evidence-based Teaching for the 21st Century Classroom and Beyond – Innovative-Driven Learning Strategies, Springer’, I have advocated for a transformation in view of the new era of AI, “Learning happens when the learners start questioning the norms, searching for information to address the varying perspectives; exploring the unknown without being spoon-fed with model answers; self-think critically on how to resolve issues at hand; experience discomfort in the process and are put in an ambiguous situation, while working towards resolving an assigned task. This allows one to think, reflect and strive toward the process of finding the answers to queries and unanswered issues. The process in the learning phase should be the primary emphasis and focus if we want to achieve high efficacy in terms of depth and quality as the outcomes”. – Rajaram, K. (2021, pp.vii)

Hence, the learning approach that is sustainable with AI must involve creation, innovation, review, build upon quality information to enhance the depth and rigor that enables the learner to be a deep, reflective, and high-order critical thinker.

o What are the potential benefits and challenges of using AI in grading and assessment in tertiary education?

Benefits 
− It provides immediate and automated feedback inclined towards the more rudimentary technical aspects, for example, flagging grammatical errors, spelling mistakes, incorrect citations, and how content structures to be improved. Hence, it frees up more quality time for educators to focus on the higher-order writing aspects like contextualized argumentation and critical, deep reasoning skills. Such spontaneous feedback makes the learners appreciate and enhance their learning process with a higher level of efficacy.

− The capability of AI to seek follow-up with probing questions till a satisfactory response is reached value-adds in how students perform their critical thinking, practice asking/probing quality questions that led to better meaningful responses, critically evaluating whether the answers are correct or not, and having them collate independently enables the assessment’s quality and standard to be placed at a much higher bar.
− On a positive lens, leveraging an AI-supported grading process helps to achieve a speedy and consistent deliverable eradicating human-related constraints.

Challenges
− In a more advanced and complex subject-related content assessment circumstance, a larger bandwidth of creative and a wide range of evaluative answers will be required and hence may potentially pose a challenge. In such circumstances, the proposed answer may not match the blueprint. This could be possibly tied to not having an adequate amount of data to pre-train and model this AI model algorithm or generally the lack of reliability and validity of the AI tool itself. 

− As there may be a lack of domain-specific knowledge used for modelling the automated grading, this creates a limitation or hindrance, for instance, technical words or phrases may be not properly and/or accurately interpreted. Hence, if the context has never been experienced and analyzed prior, an algorithm would look to see if a particular keyword exists in the answer, if it is unable to locate or do an accurate matching, then unfair results might appear. So, the accuracy largely depends on the previous data set used to train the AI, for example, there might be cases where an assessor made a mistake and graded a student incorrectly. This causes the AI supporting system to operate in a manner that may not do justice to the perform at a high level of efficacy and produce accurate, quality deliverables.

o What role might AI play in developing new teaching and learning techniques?

AI plays a vital role in deciding how the learning design and pedagogical approaches will be used to achieve a high level of learning efficacy. For example, with the intervention of AI, the teaching approach should enable them to play the role of evaluators, critical thinkers, and creators using existing knowledge. For example, using a flipped classroom pedagogical approach will enable students to collate and read the contents with AI-supported learning tools prior to the face-to-face class session, whereas, in class, they should be expected to critique the collated information to make it meaningful to the contextualized case scenarios or critique/evaluate the collated information to improve its depth, rigor, and criticalness. The learning techniques should be focusing more on the process of learning going beyond just merely content acquiring training, where the emphasis will now be shifted to the thinking process, evaluative abilities, making constructive critiques, and connecting varying perspectives to make sense of content more holistically. 

o Are there any privacy and ethical concerns with the use of AI in institutions?
Yes, certainly. Firstly, the privacy of the personal data of students and educators. The use of AI-generative tools collects and processes large amounts of personal data. This raises concerns about students’ or any users’ privacy, data confidentiality, and data security. Hence, risk arises in the usage of this data for malicious or unwanted purposes, or it may be compromised in a data breach. From the equity perspective viewed from the ethics lens, we see many AI tools are available for free, but this might change in the future. Hence, institutions advocating to adopt or leverage these tools into their assignments need to carefully consider alternative options to have all students continue their accessibility. In a similar vein, institutions must ensure and manage the fairness and equity aspects that avoid tasks that will disproportionately benefit students who can afford more expensive AI tools. Moreover, from an ethical front, it is critical to acknowledge that AI tools perpetuate biases that result in misleading, inaccurate, and/or malicious information based on the data it was trained on. Due to the large amount of data text that is being generated by AI tools and they are being trained on, it is challenging to determine and bestow accountability on the content creator, especially when the quality of content in varying dimensions is not accurate or filled with biases for example. Lastly, ethical issues may arise due to biases in the data the AI tools are being trained on. If the training data for AI incorporates biases or limitations, then the results will be also biased. This may have implications in terms of discrimination against certain groups or types of people and reinforcing pre-existing inequalities and stereotypes. 

2. The World Economic Forum Future of Jobs Report 2023 also states that employers estimate that 44% of workers' skills will be disrupted in the next five years. What impact do you think this has on student learning now? And if technology continues to change how jobs are performed, what role do tertiary institutions play in preparing students for the future?

o How do you envision generative AI tools, such as ChatGPT, changing the learning experiences of students in tertiary education?
AI tools, such as ChatGPT enable students to gain wider and more detailed information about their content search. Their access to available information becomes far easier. Hence, learning in tertiary education today should focus not merely on content acquisition rather a large focus should be on application, creation, evaluation, and higher-order thinking. 

o Will AI reshape tertiary study offerings?
Yes, in my view, it will rather adequately have a large impact progressively but rather rapidly on how the study offerings are made available. We could see more shift and inclination towards the hybrid learning design to be adopted, with e-learning elements embedded with AI tools assisting in the teaching aspects emerging. In-class interventions will include AI-embedded learning tools to enhance engagement, critical thinking, and even formative feedback for students. 

o How can students balance academic integrity while also embracing innovation with AI?
The ownership and responsibility of balancing this act now fall on students. Ethos and ethical values embedded with a strong integrity-based culture need to be developed to ensure this balance is achieved. 

o What skills do you think will be most valuable for students to have in a world where AI is becoming increasingly prevalent in the workforce?
1. Critical thinking and Problem-Solving
The workforce is hiring employees who are thinkers and knowledge workers who could leverage and effectively use highly advanced technologies and AI to deliver value for their organizations. This literally means that one has to show the ability to resolve complex issues by providing creative solutions or remedies, leveraging what the AI could fundamentally provide. This requires undoubtedly vital skills such as thinking critically with rigor and depth while the ability to have a mind that is sharp and focused on providing practical and feasible solutions. 

2. Resilience and Adaptability
AI will disrupt the way the current workplace and its related aspects function at an ever-evolving & accelerating and fast-paced speed. Hence, only those who are agile with grit and flexibility will be able to navigate this complex and dynamic environment. 

3. Developing specific skills and competencies that are not easily replicated by AI. 
The capabilities such as creativity, empathy, compassion, situational awareness with agility to adapt, and having a flexible and holistic unique worldview are some of the crucial skills that are required in the future workplace with AI becoming increasingly prevalent in the workforce. It is imperative to be competent in these skills to complement what the AI can exponentially offer at an advanced level of its ability. 

4. Capability and confidence to operate in an AI environment
The digital fluency and a high level of literacy in AI and other digital technologies is the key to having future employers see one as valuable. Primarily the emphasis here is the productivity of using these tools that certainly make one stands out of their peers.