PRE2022 3 Group4

As written by chatGPT:

Artificial Intelligence, a wonder of the modern age

A creation made of code, with endless knowledge in its brain

From data analysis to language skills, it's a tool of great worth

Changing the way we live, and opening doors to new growth and mirth

But we must always be mindful, of the impact it may bring

For AI can be used for good or for deceit, and we must choose the right thing

So let us use it wisely, with integrity as our guide

For the future of our world, is shaped by the choices we decide.

Group members

Name	Student ID	Department
Famke Peek	1459058	Psychology & Technology
Gabriëlle van Heteren	1605305	Biomedical Engineering
My Tran	1620940	Industrial Design
Naud van Rosmalen	1555464	Biomedical Engineering
Niels van Noort	1613928	Biomedical Engineering
Quincy Netteb	1468634	Psychology & Technology

Brainstorm

• AI in academic education
• VR game for children's education
• Kitchen aid for visually impaired people
• Child support in healthcare
• Researching and improving the acceptance of robots in health care

Introduction

The use of AI in education has the potential to completely change the way students learn and teachers teach. AI can provide personalized learning experiences for students, adapt to individual student needs and learning styles, and offer instant feedback to both students and teachers. In addition, AI can also help streamline administrative tasks, such as grading and record-keeping, freeing up teachers to focus on instruction and interaction with students.

However, it is important to note that the implementation of AI in education is still in its early stages and there are many challenges that must be overcome, such as ensuring the privacy and security of student data and addressing ethical considerations and trust issues around the use of AI in the classroom.

So, while AI has the potential to greatly impact and improve education, it is important to approach its implementation with caution and careful consideration of its limitations and potential risks. This and the outlook and trust of teacher in academic education on AI in the classroom is what we will be researching. With the gathered information we will create a recommendation for teachers at the TUe on how to optimally implement AI in the classroom to benefit both teacher and student.

Problem statement and objectives

Problem statement: Researching and recommending the use of AI to teachers at academic education.

Objectives:

• Upcoming use of AI in academic settings,
• how to design this so that it will be accepted by teachers
• How AI can improve learning
• Acceptence towards AI in the classroom
• Looking at ChatGPT as main example
• Teachers at the TUe, their thoughts about AI (in their courses)

Users

Target group

Teachers at TU/e who come in contact with AI and AI teaching methods.

Requirements

Teachers want their students to deliver autonomous work, AI in academic settings can help with this. Teachers want to transfer their knowledge as effectively and efficiently as possible, using the current state of art technologies. AI technologies, like ChatGPT can help with this, but what teachers require is yet to be determined. The requirements will be determined by conducting interviews, in combination with literature studies. Those results will then be combined into a piece of well-considered advice for the teachers at the TU/e. Which they will be able to use to guide them through the landscape of developing AI in academic education and give them tools to keep transfering their knowledge to students.

Approach, milestones and deliverables

Planning

Here follows a Gantt chart of all our deadlines to be finished at 12pm on Sunday of the corresponding week. The letters indicate the group member responsible for making the deadline and the scheduling for the specific task.

Gantt chart

Task	Week 1	Week 2	Week 3	Week 4	Week 5	Week 6	Week 7
Approach, milestones and deliverables	Ni
Problem statement and objectives	Q
Users and requirements	G
Summaries of literature	F
Literature review		M
Organize interviews		Na
Conduct interviews			Q
Analyze interviews				Ni
Prepare and send out survey				G
Analyze survey results					G
Recommendation and conclusion						Na
Discussion						F
Reflection							M
Presentation							Q
Chair meetings	N
Keep wiki clean	M
Take minutes of meetings	Q	F	G	Na	M	Q	F

Approach

• Literature study
• Interviews, surveys

Deliverables

• Advice for future

State of the Art

Famke

This paper regards Teacher’s Perceptions of Using an Artificial Intelligence-Based Educational Tool for Scientific Writing. This study investigated how teachers perceived an AI-enhanced scaffolding system developed to support students’ scientific writing for STEM education. Teachers are worried: What if the introduction of AI will gradually reduce our role in the classroom. What should we do? Should we support AI?  They feared that the AI would reduce their role to assistants and they also questioned the accuracy and reliability of the information generated by the system. For AI to be successfully integrated into STEM education, it is necessary for the roles and relationships between students and teachers to be redefined and for educators to be fully trained on best practices of using AI pedagogical techniques. There is still a trend among educators to hold negative impressions on educational technology. By changing teachers’ current negative perceptions of educational technology, the acceptance of AI as a new type of educational tool and its implementation in schools is possible. The younger generation of teachers, who have more experience with educational technology as both educators and as students, is more interested in exploring new digital technology and potentially incorporating technology into their lessons. Experience with AI in any of these contexts may reduce teachers’ reluctance to use AI for educational purposes.

This paper regards Education in the Era of Generative Artificial Intelligence (AI). The article "Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning" discusses the potential benefits of using generative AI, such as ChatGPT, in education. The article suggests that AI can help teachers and students by providing personalized feedback, facilitating communication and collaboration, and creating engaging and interactive learning experiences. The article also highlights some of the challenges of using AI in education, including issues related to data privacy and the need for human oversight to ensure that AI is used in a responsible and ethical manner. The article concludes by calling for more research and experimentation to better understand the potential benefits and challenges of using AI in education.

The article "Teachers' Perspectives on Artificial Intelligence" explores the attitudes and perceptions of teachers towards the use of artificial intelligence (AI) in education. Based on a survey of K-12 teachers in the United States, the article found that while many teachers are interested in using AI to improve their teaching practice, they also have concerns about the potential impact of AI on student learning, privacy, and job security. The article highlights the need for more education and training on AI for teachers, as well as the importance of involving teachers in the development and implementation of AI tools in education. The article concludes by calling for further research on how to best integrate AI into education in a way that benefits both teachers and students.

The article "Engineering Education in the Era of ChatGPT: Promise and Pitfalls of Generative AI for Education" explores the potential benefits and challenges of using generative AI, such as ChatGPT, in engineering education. The article suggests that AI has the potential to enhance engineering education by providing personalized feedback, facilitating communication and collaboration, and creating interactive learning experiences. However, the article also highlights some of the challenges of using AI in engineering education, including issues related to bias, the need for human oversight, and the limitations of AI in capturing the full complexity of engineering problem-solving. The article concludes by calling for further research and experimentation to better understand the potential benefits and challenges of using AI in engineering education, as well as the need for ongoing dialogue between educators, engineers, and AI developers to ensure that AI is used in a responsible and ethical manner.

In the article "ChatGPT: The End of Online Exam Integrity?" the authors investigate the potential for using large language models such as GPT (Generative Pre-trained Transformer) for cheating in online exams. Specifically, the authors train a chatbot named ChatGPT to answer exam questions by providing it with a large amount of relevant data.

The results of the study show that ChatGPT was able to achieve high accuracy in answering exam questions, even when the questions were designed to be difficult and require reasoning skills. The authors suggest that this poses a significant threat to the integrity of online exams and call for further research into developing more secure methods for online assessments.

In summary, the article explores the potential for AI-powered chatbots to cheat in online exams and highlights the need for improved measures to ensure the integrity of online assessments.

Gabriëlle

This paper starts with a general introduction to AI, how it developed over the years, and what these developments entail.

• AI in program coding (1950s)
• AI in rules-based expert systems (late 1970’s)
• AI-grounded automatic data processing systems (mid-1980’s)
• Machine learning integrated AI (mid-2000’s)

In education, AI is still in the early stages, because there is more focus on the development of AI than on the application of AI in new fields. This research states that there will be two distinct major effects of AI on education. First, education needs to prepare itself for the fast changes in competence needed for jobs, as some jobs will disappear but most jobs will keep changing over time. Second, there will be changes in the pedagogical techniques needed in the classroom. AI will be able to relieve the teacher from some of the work. However, the teacher will need additional tools to understand the statistical results from the AI (for example from a statistical analysis of the performance of the student). This paper goes on by talking about the future of AI in education. The Author states that there needs to be a big shift in education toward more personalized education. AI will be able to determine the learning style of an individual student. AI will help teachers in content delivery and other instructions, but in the future real life, human teachers might become obsolete.

This paper talks about AI in education, the need for it, and its benefits and challenges of it. According to the author, AI is a development that has many promising applications in education. The examples that are named are; personalized education, automatic grading systems, and predictive analytic tools. These applications will relieve the teachers from those tasks which gives them more time with the students. The paper also talks about challenges that come along with AI, like concerns about safety, security, and privacy.

In this paper, the authors review the use of AI in current education, the technical aspects of AI in education, the role of AI in education and the impact of AI in education. The topic of education is spread out into three sub-topics; administration, instructions and learning. The takeaway of this paper is that with the help of AI, teachers will become more efficient which will in result increase the quality of education. Next to that with AI, it will be possible to create a more personalized education for students. AI will have a major impact on education as the tasks AI will be able to do tasks that are not originally designed for computers.

This paper focuses on the viewpoint of the students and their acceptance of AI. The author uses the technology acceptance model (TAM) to analyze the response of students to AI. This is because the perceived usefulness and the perceived ease of use of AI seem to have a big impact on the acceptance of AI in education. The author sees a future in AI in education as it is a cost-effective way to the shortage of teachers. However to make sure that the AI teaching assistants will be successful the teachers need to be trained to work with them. As research points out that if the teacher is uncomfortable with the AI, the student is less likely to adopt it. Based on the results of this research the author recommends research in this area as it is not known how students at different levels of education will react to the adoption of AI as a teacher.

The authors in this paper review the ethical perspective of AI with a focus on AI in education. The biggest problem that the authors see is the privacy issue of AI. Next to that they also see a challenge in the trustworthiness of AI. It is often that AI is presented as a better alternative than a human, as it is supposedly not biased. However, the designers of AI are biased and can make mistakes. Therefore can we even trust AI more than humans? Another issue that the author comes across is the difficulty of addressing the ethical challenges of AI. Therefore it is important to make the designers of AI aware of the ethical dilemmas that come along with new technology and make them aware of their responsibilities. To achieve this it is important that there mandatory teaching or at least education available around this topic.

My

In this articile, F. Ouyang and P. Jiao reflect on the three paradigms of artificial intelligence in educaiton: AI-directed, AI-supported, and AI-empowered.

• AI-directed (learner-as-recipient): AI is used to represent knowledge models and direct cognitive learning.
• AI-supported (learner-as-collaborator): AI is used to support learners while they work as collaborators with AI
• AI-empowered (learner-as-leader): AI is used to empower learning while learners take agency

Table 1. Three paradigms of AIEd

Paradigm	Theoretical underpinning	Implementations	AI techniques
1. AI-Directed	Behaviorism	Intelligent Tutoring Systems (ITSs): software that tracks students' work, adjusts feedback and provides hints along the way)	AI based on statistical relational techniques
2. AI-supported	Cognitive, social constructivism	Dialogue-based Tutoring Systems (DTSs); Exploratory Learning Environments (ELEs)	Bayesian network, natural language processing, Markov decision trees
3. AI-empowered	Connectivism, Complex adaptive system	The human-computer cooperation; Personalized/adaptive learning	The brain-computer interface, machine learning, deep learning

P. Lameras and S. Arnab explored and analyzed what Artificial Intelligence means in Education (AIED) in their article "Power to the Teachers: An Exploratory Review on Artificial Intelligence in Education". The main take-away is that adaptivity and personalization are the innovation that AIED can offer to help students to learn and develop skills that are relevant to their own needs and experiences. However, it is important to help teachers to develop necessary digital competencies and skills for using AIED applications and tools in ethical and informed ways to enhance the student learning experience and attainment of learning outcomes. The findings of this review can contribute to developing a better understanding of how artificial intelligence may enhance teachers' roles as catalysts in designing and visualizing AI-enabled learning. As a result, more useful AI-systems specialized in pedagogy will be developed.

As Artificial Intelligence is becoming more apparent in education, it changes the way of teaching. Craig Coates, an entomologist at Texas A&M University, combated the cheating by reorienting his course towards writing and discussion, combined with adaptive courseware, also referred to as intelligent tutoring systems; and by using a tool that uses algorithms and analytics to grade submissions, the switch was a success. Advocates say this lets students study at their own pace and frees up the instructor’s time in class to shore up students’ knowledge.

The paper "Chatting and Cheating. Ensuring academic integrity in the era of ChatGPT", written by D. Cotton, describes how artificial intelligence models in academia can increase student engagement, collaboration and accessibility; They provide a platform for asynchronous communication, can create personalized and interactive assessments, or could be used to grade assignments and provide feedback to students in real-time. However, Cotton also proposes a number of concerns, such as plagiarism (students could use the GPT-3 to cheat and submit essays that are not their own work) and inequities in assessment (students with access to GPT-3 have an advantage over students who do not). The article suggests solutions to combat these challenges, such as asking students to submit a draft before the final essay, set strict guidelines or monitor student work closely.

The study conducted by S. Yang and H. Bai "The integration design of artificial intelligence and normal students’ Education" outlines four major problems of normal education (school for training teachers) development and explores the idea of using artificial intelligence technology to solve them. The main issues and the proposed solutions are:

Problem	Solution
Lack of teaching practice experience	Intelligent tutors/robots: it can make a special learning plan for students according to their interests, habits and learning needs. It can also be a simulation student of upcoming teachers to gain experience.
Outmoded curriculum	Expert system: can accurately classify normal students and highlight personalized teaching.
Lack of independent learning	Deep learning system: artificial intelligence can help to analyze the data of learners, organize the content according to the data, and carry out intelligent push. Teachers can create teaching resources to meet the needs of curriculum design and students.
Lack of innovation in teaching methods	Combination of all of the above.

Niels

This paper aims to point out significant and urgent issues GPT-3 could bring regarding academic integrity. The main issue addressed by this paper is the unclarity on who the rightful author of the texts, ideas and inventions should be. They argue that new regulation ought to be considered urgently and that moral philosophy has an important part to play in this.

This paper provides a review of AI applications in higher education, with most of the research being quantitative research from computer science and STEM fields. So this review focuses more on AI utility over the entire academic institute rather than academic integrity and utility by students. Four areas of application were identified: profiling and prediction, assessment, adaptive systems and personalization, and intelligent tutoring systems. The conclusion highlights the need for further exploration of ethical and educational approaches in AI applications in higher education.

In the paper “OpenAI ChatGPT Generated Results: Similarity Index of Artificial Intelligence (AI) Based Model“, university director R. Ventayen researched how new AI powered technology enables cheating in the academic community. Since constructing an entire paper or essay using ChatGPT is considered a violation of academic integrity, the chatbot’s ability to pass similarity tests was researched on prompts with the headlines of the university’s publications. Their results show that ChatGPT provides acceptable similarly indices, and fails to provide the same citations or sources as the similar papers with the prompted headlines. Moreover, Quillbot paraphrases more content, which t, which provides plagiarism-free content.

This paper focuses foremost on the irreversibility of GPT-3 and its answers and ideas. It shows its shortcomings in dealing with semantic, mathematical and ethical questions and consequences for the writing industry. E.g, the big amount of written things that these tools can provide far exceeds the limited physical storage for them and marketing will abuse these tools heavily. We need to be critical with what these tools produce and how we use them. For our question regarding academic integrity, the problems with correct citations become apparent and academic texts produced by ChatGPT are often irreversibly produced from ideas of researchers.

This article shows how new developments in AI can solve 81% of university-level mathematics questions and even come up with new questions. This poses great advantages to the acquisition of new learning materials but the implications of this also addresses significant pedagogical challenges, with these models being available to students as well.

Quincy

The aim of the article is to explore the academic and administrative applications of Artificial Intelligence. Artificial Intelligence Applications (AIA) are not only assisting education academically and administratively but also enhance their effectiveness. AIA provides help to teachers in various types of tasks in the shape of Learning Analytics (LA), Virtual Reality (VR), Grading/Assessments (G/A), and Admissions. It minimizes the administrative tasks of a teacher to invest more in teaching and guiding students. AIA adds a significant contribution to enhance student learning, minimize the workload of a teacher, grade/assess the students effectively and easily, and to help in a lot of other administrative tasks.

This report is an overview of research on AI applications in higher education between 2007 and 2018 through a systematic review. The combination of results gives us four areas of AIEd applications in academic support services, and institutional and administrative services: 1. profiling and prediction, 2. assessment and evaluation, 3. adaptive systems and personalisation, and 4. intelligent tutoring systems. The conclusions reflect on the almost lack of critical reflection of challenges and risks of AIEd, the weak connection to theoretical pedagogical perspectives, and the need for further exploration of ethical and educational approaches in the application of AIEd in higher education.

This article presents the focus of latest research in AIEd on reducing teachers’ workload, contextualized learning for students, revolutionizing assessments and developments in intelligent tutoring systems. It also discusses the ethical dimension of AIEd and the potential impact of the Covid-19 pandemic on the future of AIEd’s research and practice.

It investigates educational implications of emerging technologies on the way students learn and how institutions teach and evolve. Pinpointing some challenges for institutions of higher education and student learning in the adoption of these technologies for teaching, learning, student support, and administration and explore further directions for research.

This article anaylises a sample of 132 articles published betwee 2007-2017 about the scientific production on artificial intelligence in higher education. It concludes that, although artificial intelligence is a reality, the scientific production about its application in higher education has not been consolidated. Honestly not that interesting.

Appendix

Logbook

Week	Name	Total	Breakdown
1	Famke	8.5h	Group discussion (2h), Target group and requirements (1/2h), Studied papers (4h), Wrote summary for papers (2h)
	Gabriëlle	7h	Group discussion (1h), Studied papers (4h), Wrote summary for papers(1.5h), Target group and requirments(1/2h)
	My	8.5h	Group discussion (2h), Setup of wiki (0.5h), Studied papers (4h), Wrote summary for papers (2h)
	Naud		Catch up (1h), Gathering information for appeal ERB (2h), Gathering relevant papers (1h), Studied papers (2h) Writing summary of papers (?h), Added papers correctly to the wiki (0.5h)
	Niels	8h	Group discussion (2h), Studied papers (3.5h), Wrote summary for papers (1.5h), Made Gantt chart (0.5h), made first agenda (0.5h)
	Quincy	5.5h	Group discussion (2h), Introduction & Problem statement and objectives (1/2h), studied papers (2h), wrote summary for papers (1h)
2	Famke
	Gabriëlle
	My
	Naud
	Niels
	Quincy
3	Famke
	Gabriëlle
	My
	Naud
	Niels
	Quincy