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: How could the use of ChatGPT affect students in reaching the learning goals of the course 4WBB0 at the TU/e?

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

The target group of this project are the teachers of the TU/e who designed and teach the course engineering design (4WBB0) and students who followed this course. In this research the perspective of the teachers and students on the use of chatGPT in this course is reviewed. The input of students will be used to get a better image of how students intend to use chatGPT. The input of the teachers will be used to understand the learning objectives of the course engineering design and to determine the effect of chatGPT on those learning objectives. The end product will be a deliverable useful for the course coordinators of engineering design.  

Requirements

Teachers want their students to deliver autonomous work, ChatGPT 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 distributing surveys among students of the TU/e and conducting interviews with teachers, based on the survey results, 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, consisting of guidelines for a course for the teachers of how to make exercises and tests for students that can benefit from using ChatGPT, but not be made solely with ChatGPT. Which they will be able to use to guide them through the landscape of ChatGPT use in academic education and give them tools to keep transferring 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

ChatGPT is a new technology, but has been extensively researched, as it is such a noticeable new technology. ChatGPT is an acronym for Chat Generative Pre-trained Transformer and was created in November 2022. It is based on the OpenAI GPT-3 engine and has been fine-tuned by supervised and reinforcement learning technology; this means that the AI learns by having humans simulate artificial conversations with it and adapting its responses based on how accurately they reflect natural human dialogue. ChatGPT is also able to remember previously given prompts in the same conversation, making it a more personalized chatbot compared to its alternatives. ChatGPT has a lot of functionalities, for example:

• Write and debug code, generate scripts and functions

• Give detailed explanations on complex topics (answer test questions)
• Solve mathematical problems
• Write texts in different styles (write student essays)
• Compose music
• Explain mathematical theorems
• Play games like tic-tac-toe

However, the technology is not without its limitations. It has the potential for over-optimization due to its reliance on human oversight, also known as Goodhart's law, which could hinder performance. Furthermore, language models like ChatGPT are prone to writing plausible-sounding but incorrect answers, which is called artificial intelligence hallucination; this can be attributed to insufficient training data. The AI is also limited by a lack of knowledge about events that occurred after 2021 and in some cases suffers from algorithmic biases. Furthermore, although ChatGPT is able to produce results that seem genuine, it is unable to fully comprehend the complexity of human language and instead relies solely on statistical knowledge and patterns.

Research into ChatGPT still has a long way to go. vVan Dis, E. et al. have proposed five priorities for future research on ChatGPT:

• The first priority is to explore the ethical implications of AI-generated content and to develop guidelines for responsible use.
• The second priority is to investigate the limitations of ChatGPT and to develop methods for detecting and addressing bias in its outputs.
• The third priority is to improve the interpretability of ChatGPT and other NLP models, making it easier to understand how they arrive at their outputs.
• The fourth priority is to investigate the potential of ChatGPT in domains beyond language, such as image and video analysis.
• Finally, the fifth priority is to develop more efficient and sustainable methods for training and deploying ChatGPT, in order to reduce its carbon footprint and energy consumption.

In order for reserach into ChatGPT to advance however, collaboration across disciplines on ChatGPT and other AI systems is very important.

ChatGPT in academic education

Artificial intelligence has been a rapidly growing field in recent years, and the development of large language models like ChatGPT has been at the forefront of this expansion. These models have the potential to revolutionize the way we access and use information, particularly in educational contexts. However, they have also raised concerns about issues like academic integrity, student engagement, and the role of teachers in the learning process. To address these concerns, researchers have conducted various studies and published papers on the implications of ChatGPT for education.

ChatGPT has the potential for using large language models such as GPT for cheating in online exams. For instance, a recent study demonstrated that a chatbot named ChatGPT tried 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.

Another issue that comes up regarding academic integrity, is the unclarity on who the rightful author of the texts, ideas and inventions should be. Currently, there is no clear consensus on who should be considered the rightful author of AI-generated content. This is a complex issue that requires input from experts in moral philosophy, law, and computer science.

One more issue regards plagiarism when using ChatGPT. A study into this examined the accuracy and originality of scientific abstracts generated by ChatGPT compared to those produced by human experts. The study used a combination of artificial intelligence output detectors, plagiarism detectors, and blinded human reviewers to analyze the abstracts. The results showed that ChatGPT-generated abstracts had a higher similarity score with original abstracts than with other sources, but also revealed some cases of potential plagiarism. This suggests the need for caution when using AI-generated abstracts in scientific research. In the academic world, artificial intelligence models are gaining popularity due to their ability to enhance student engagement, collaboration, and accessibility. A paper authored by D. Cotton, explores the potential benefits and challenges of using AI in education. The models provide a platform for asynchronous communication, personalized and interactive assessments, and real-time grading and feedback. However, also according to D. Cotton there are concerns about academic integrity, particularly the possibility of plagiarism. With access to GPT-3, students could submit essays that are not their own work. Additionally, there are concerns about inequities in assessment, as students with access to GPT-3 have an advantage over those 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.

Another paper explored the broader implications of ChatGPT for traditional models of education. The author argued that AI systems like ChatGPT have the potential to disrupt the traditional "banking model" of education, in which knowledge is transmitted from teacher to student. Instead, learners could access knowledge and information more directly through AI systems, which could democratize access to education and make it more inclusive. The author emphasizes the need for educators to adapt to this changing landscape and to shift their focus towards fostering critical thinking, creativity, and other skills that cannot be easily automated, and suggests that AI systems like ChatGPT have the potential to democratize access to education, making it more accessible and inclusive for learners around the world.

Furthermore, a paper written by Rudolph also explores the implications of chatGPT for both students and teachers. While chatGPT offers personalized AI tutoring for students, it also has the potential to reduce the workload for teachers, especially with the use of automatic assessment tools. Furthermore, it can help teachers analyze their students' skills more easily. The paper gives a general overview of challenges and opportunities:

Challenges of AI in education	Opportunities of AI in education
Teachers are afraid students will outsource all their work to chatGPT.	Opportunity for teachers to improve/change their assessment and teaching techniques.
ChatGPT doesn’t evaluate the relevance of the information, it just generates text that is an imitation of what it has learned.	“ChatGPT allowed students to learn through experimentation and experience”

To look further into the fear of teachers that students will outsource all their work to ChatGPT, we will look another paper written by García-Peñalvo that reviews previous literature on ChatGPT. The most controversial issue with ChatGPT is the possibility of students using it as an easy solution to write essays without putting in the necessary effort. Because of this, they won’t acquire the needed knowledge for their course. However, the problem might not be the tool itself, but that the assessment techniques of educational institutions have become outdated However, the paper argues that prohibiting chatGPT is not the way to go. Instead, teachers and students should learn how to use the tool to their advantage.

As mentioned times before, ChatGPT has it obvious limitations. A controversial view in this paper written by Thorp, the author of the article is not necesseraly worried about the use of chatGPT in education as ‘it did well finding factual answers, but the scholarly writing still has a long way to go’. He thinks it pushes academics to design their courses in such a way that they are not easily solved by AI. The author is more worried for the influence of chatGPT on the world of literature.

While chatGPT has its limitations, it has the potential to replace humans in routine tasks such as homework grading, potentially spelling the end of traditional essay writing assignments. "ChatGPT User Experience: Implications for Education" explores the user experience of chatGPT and its potential impact on education. He also states that using AI tools to perform certain tasks ‘should be a part of the educational goals in the future’. The author concludes that teachers need to change their assignments to make it harder for students to use AI, but also notes that using AI in assignments to engage students in learning is a viable option.

To summarize, ChatGPT is a powerful tool with many functionalities, from writing texts and composing music to solving mathematical problems and playing games. However, it is not without its limitations, such as over-optimization, algorithmic biases, and the potential for incorrect responses due to insufficient training data. The future research priorities include exploring the ethical implications of AI-generated content, detecting and addressing bias in its outputs, improving the interpretability of ChatGPT and investigating the potential of ChatGPT in domains beyond language.

In academic education, ChatGPT has the potential to revolutionize the way we access and use information, but it also raises concerns about academic integrity, student engagement, and the role of teachers in the learning process. Further research is needed to develop secure methods for online assessments and determine the rightful author of AI-generated content. Despite the challenges, AI systems like ChatGPT have the potential to democratize access to education and make it more inclusive.

Survey questions

Research into ChatGPT

In order to review the potential of using ChatGPT in academic education, we would like to know your experiences with the technology as well as your opinion on it. We will focus on the course Engineering Design, a mandatory course where you go through a complete design process, from the first idea to the realization of the product. We will look at how ChatGPT can be used for this course.

This survey is conducted for the course Project Robots Everywhere (0LAUK0), and its results will be used to shape further investigation in academic regulations regarding AI. The results of the questionnaire will be anonymous and it will take approximately 5-10 minutes to complete.

Do you give consent to participate in this study?

• Yes
• No

Knowledge of ChatGPT

Have you heard of ChatGPT before?

• Yes
• No

Do you know the capabilities of ChatGPT?

• Yes
• No

Could you name some of these capabilities?

• Open question

To give you an idea of what ChatGPT is, please read this:

ChatGPT is a large language model developed by OpenAI. It stands for “Generative Pre-training Transformer” and uses deep learning technology to generate text and respond to questions in a human way.

The model is trained on a large amount of text data, making it capable of understanding context and semantics. This makes ChatGPT a popular choice for chatbots, virtual assistants and other applications where human interaction is required.

Some examples of what ChatGPT can do:

- Write emails

- Write essays and academic reports

- Write poetry and song lyrics

- Compose music

- Answer (test) questions and solve problems

- Generate lines of code based on a prompt

- Answer customer queries

Usage of ChatGPT

Have you used ChatGPT before?

• Yes
• No

How often have you used ChatGPT?

• Only once or twice
• Monthly
• Weekly
• Daily

For what have you used ChatGPT?

• Open question

How would you rate your experience with ChatGPT in general?

• Rating from 0 to 5

How would you rate your experience with ChatGPT as an academic tool?

• Rating from 0 to 5

ChatGPT in academic education

Have you ever used ChatGPT for academic purposes? If yes, for what course(s)?

• Open question

Would you say usage of ChatGPT should be considered your own original work (so no plagiarism)?

• Yes
• No

When should the use of ChatGPT be considerd as plagiarism?

• Open question

Looking back, would you think ChatGPT could be a good addition to the course engineering design?

• Yes
• No

Please, if possible, elaborate on why? (Elaboration on previous question)

• Open question

For what do you think ChatGPT CAN be used in the course engineering design?

• Open question

For what do you think ChatGPT SHOULD be able to be used in the course engineering design?

• Open question

Learning objectives of Engineering Design

How likely do you think you would be able to reach the following learning objectives of Engineering Design with the use of ChatGPT? (Very likely - Very unlikely)

• Execute a generic design process
• Formulate a design goal
• Define the functional and technical specifications
• Generate an elaborate list of realization possibilities for the different functions of the design
• Select a number of design concepts from an extensive list of realization possibilities
• Make a final design choice between a number of concepts
• Develop a detailed design that meets the specifications
• Develop and execute a test plan for the prototype
• Evaluate a prototype based on test results and give an advice for redesign
• Reflect on the design and on the design process
• Write a design report describing the design process, the foundation of the choices made and the evaluation of the delivered design

Additional Learning Objectives

How likely do you think you would be able to reach the following learning objectives with the use of ChatGPT? (Very likely - Very unlikely)

• Gaining insight in designing a simple computer program
• Giving and understanding simple mathematical proofs
• Understand how basic electrical and electronic circuits work

Feelings about ChatGPT

What are your feelings regarding ChatGPT? (Strongly disagree - Strongly agree)

• I see ChatGPT as having/could have had a positive influence on my engineering design project
• I would have seen ChatGPT as a usefull tool for my engineering design project
• I see ChatGPT as a shortcut for tedious tasks I would have/had to perform in the course engineering design
• I will use/would have used ChatGPT in the course engineering design regularly
• I feel like I would have learned something when using ChatGPT for the engineering design project

Interview script

Interviewee: [name] Date: [date]

Interviewer: [name] Location: [location]

Introduction

Hi, my name is ___ and I’m conducting this interview as part of our project for the course Project Robots Everywhere.

The goal is to review the potential of using ChatGPT, an AI chatbot, in academic education, so we would like to know your experiences with this technology as well as your opinion on it. We will mainly focus on the course Engineering Design and will look at how ChatGPT can be used for this course.

1. What is your name?
2. What is your function / role within Engineering Design? (lecturer, tutor, etc.)

Knowledge and experience

Before we go into the specific course, we’d like to know what your knowledge and experience is regarding ChatGPT

3. Have you heard of ChatGPT before?

4. Do you know its capabilities?

a. If yes, give examples

[Explain capabilities, show examples]

Some examples of what ChatGPT can do:

• Write emails
• Write essays and academic reports
• Write poetry and song lyrics
• Compose music
• Answer (test) questions and solve problems
• Generate lines of code based on a prompt
• Answer customer queries

5. Have you ever used ChatGPT before?

a. If yes, what for?

b. Have you ever used ChatGPT as an academic tool?

c. How would you rate ChatGPT as an academic tool?

d. How would you describe your overall experience with ChatGPT?

ChatGPT in academic education

Now we will go more in depth about the potential usage of ChatGPT in academic education, and more specifically, Engineering Design.

6. What is your opinion on using ChatGPT as an academic tool?

7. What is your expectation for the future of academic research with these AI technologies on the rise? Do you believe the course should change to reflect this?

8. How do you think chatbots like ChatGPT would influence students’ ability to write? Does this also affect their ability to write code?

9. Does using ChatGPT count as plagiarism in your opinion?

10. Would you be open to using / allowing your students to use ChatGPT in your course?

a. If yes, how would you implement it? Would you actively encourage it

b. If no, why?

11. Would the learning objective of Engineering Design still be obtainable when using ChatGPT?

a. Which ones will become “useless” since automation is becoming more generalized? (for example, writing simple code)

b. What would you change about the learning objectives? (make them more complex?)

c. How would you adjust the assignments to fit the new criteria?

12. What would you think of giving students an assignment in which they are required to use ChatGPT?

13. In your opinion, does ChatGPT make the education of students better, or does it hinder them in their development?

Survey input

t.b.d.

Theory

ChatGPT is a large language model developed by OpenAI. It stands for “Generative Pre-training Transformer” and uses deep learning technology to generate text and respond to questions in a human way.

Some examples of what ChatGPT can do:

• Write emails
• Write essays and academic reports
• Write poetry and song lyrics
• Compose music
• Answer (test) questions and solve problems
• Generate lines of code based on a prompt
• Answer customer queries

Possible questions

• How do you think chatbots like ChatGPT would influence students’ ability to write?
• What would you think of giving students an assignment in which they are required to use ChatGPT?
• Does using ChatGPT count as plagiarism in your opinion?
• In your opinion, does ChatGPT make the education of students better, or does it hinder them in their development?

Background literature

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.

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.

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 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.

Artificial intelligence and natural language processing systems are becoming increasingly prevalent in various forms of writing. These natural language processing (NLP) systems are trained on large databases of text to produce and refine statistical models that generate natural language responses. However, NLP systems do not "know" the meaning of the text they generate and can make factual and reasoning mistakes, which raises issues of accountability for authors using these systems. The use of NLP systems also raises questions of transparency in regards to authorship credit and contributions, and must be acknowledged in the text and references section of the manuscript.

The first chapter of this book aims to determine the knowledge and skills that remain for humans in an AI-driven world. It addresses AI's impact on education and highlights the need to develop awareness and understanding of AI. The goal is to create an educational environment where AI supports learners and teachers and prepares students for an AI-dominant future.

This article discusses recent developments in policies for medical journal publishing and editing in Korea. The article highlights that many editors in Korea are also publishers and therefore need to keep up with current trends and policies in the industry. The article focuses on six main policies that have emerged, including the use of artificial intelligence tools in publishing, preprint publications, open peer review, model text recycling policies, the updated 4th version of the Principles of Transparency and Best Practice in Scholarly Publishing, and the recommendation to include country names in human studies titles. The article also mentions that the use of AI in writing has increased, including in peer review and plagiarism detection. This shows the current and expected relevance AI has in modern scientific writing.

OpenAI launched a preview version of ChatGPT. It is part of the GPT (Generative Pre-trained Transformer) technology that can generate human-like text based on internet data. The release of ChatGPT sparked discussions on the impact of AI on education, with some saying it could render the student essay obsolete and others expressing concerns about cheating and false information. Despite its promise of transforming education, ChatGPT was criticized for its lack of understanding of meaning and content and its association with environmental racism and the interests of tech elites. Some educators called for better assignments that can't be written by an algorithm and for teaching students to use AI ethically. Access to ChatGPT was blocked by some US education departments due to concerns of dependence on technology, loss of privacy, and misuse of AI. This article opens up a range of important issues that are relevant across the educational field.

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.

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.

The paper is about a pedagogical experiment in which undergraduates were assigned to "cheat" by using text-generating AI software (GPT-2) to write their final class essay. The students were asked to reflect on the ethics of using AI in this way, such as what counts as plagiarism, and how working with AI could change their perspectives on writing, authenticity, and creativity. The results showed that composing with GPT-2 opened up the students' perspectives on the ethical use and evaluation of language models, and that their insights on these issues were connected to broader conversations in the humanities about writing and communication. The author of the paper shares the students' experiences and reflections on the experiment.

Survey

https://forms.office.com/Pages/DesignPageV2.aspx?subpage=design&FormId=R_J9zM5gD0qddXBM9g78ZOciNcKFkhVJsg7I7H6kiF5UNzNXQzhaOEpWSjZJSDg1WUZBN1lWTkkwUS4u

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	9h	Catch up (1h), Gathering information for appeal ERB (2h), Gathering relevant papers (1h), Studied papers (4h) Writing summary of papers (1h)
	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	7.5h	Group discussion (2h), Introduction & Problem statement and objectives (1/2h), studied papers (4h), wrote summary for papers (1h)
2	Famke	5.5h	Group discussion (1h), Target group and requirements (1/2h), Searched for literature (2h), Wrote summary for papers (2h)
	Gabriëlle	7h	Group discussion (1h), Searched for literature (1/2h), Studied papers (3h), Wrote summary for papers (1.5h), Group discussion (1/2h), Prepared for tutor meeting(1/2h)
	My	7h	Group discussion (1h), Searched for literature (1/2h), Studied papers (2h), Wrote summary for papers (1h), Read and organized already studied literature (2.5h)
	Naud	4.5h	Group discussion (1.5h), Filled in ERB review form (3h)
	Niels
	Quincy
3	Famke	3h 20m	Tutor meeting (20 min), Group discussion (1h), Worked on survey (2h)
	Gabriëlle		Tutor meeting (20 min), worked out target group (40 min)
	My
	Naud		Group discussion (1h), Filled in ERB review form (1h), Changed research question and stakehoders (0.5h)
	Niels
	Quincy
4	Famke		Tutor meeting (20 min), Group discussion (2.5h), Working on state of the art (4h)
	Gabriëlle
	My
	Naud		Tutor meeting (20 min), Group discussion (2.5h), ERB form correspondence (0.5h), updating wiki with survey questions(1h)
	Niels
	Quincy
5	Famke
	Gabriëlle
	My
	Naud
	Niels
	Quincy