Source 1
Halkiopoulos, C., & Gkintoni, E. (2024). Leveraging AI in E-Learning: Personalized Learning and Adaptive Assessment through Cognitive Neuropsychology—A Systematic Analysis. Electronics, 13(18), 3762.
Database used: Google Scholar
Search terms used: artificial intelligence, online learning, bias
Why this source is relevant to your research question: This article is relevant because it looks at how AI chatbox programs in e-learning help personalized learning and adaptive assessments for writing assignments. The article explores how AI are adaptive and can provide instant recommendations that are customized critiques to students for improving their writing skills. It also warns that being dependent on AI chats could hinder creativity and critical thinking, both of which are crucial to understanding how AI chats impact online courses.
Source 2
Guilherme, M., et al. (2020). The Impact of Artificial Intelligence on Learner-Instructor Interaction in Online Learning. International Journal of Educational Technology in Higher Education, 17(1), 48-60.
Database used: Google Scholar
Search terms used: artificial intelligence, online learning, bias, limitations.
Why this source is relevant to your research question: This article is relevant because it shows how the help of AI programs can affect and influence how students and instructor’s interactions take place on online courses. It mentions how AI programs can give students instant feedback, grades, and critiques on their writing, which takes away the need for the teacher to constantly give feedback. By limiting involvement, this can be harmful, while AI may impact creativity and learning capabilities.
Annotated Bibliography
Source 1
APA Citation:
Halkiopoulos, C., & Gkintoni, E. (2024). Leveraging AI in E-Learning: Personalized Learning and Adaptive Assessment through Cognitive Neuropsychology—A Systematic Analysis. Electronics, 13(18), 3762. https://doi.org/10.3390/electronics13183762
This article explores AI programs that are used in online learning and that are personalized and adaptive to users. It talks about how AI programs are made to help students learn better by making changes to their writing assignments based on their needs. However, it explains how the interaction between instructor and student can be harmful to writing skills by providing adaptive help; they warn that relying on it may have a negative impact on critical thinking and creativity.
Source 2
APA Citation:
Seo, K., Tang, J., Roll, I., Fels, S., & Yoon, D. (2021). The impact of artificial intelligence on learner–instructor interaction in online learning. International Journal of Educational Technology in Higher Education, 18(1). https://doi.org/10.1186/s41239-021-00292-9
This article examines the impact chatbots have on how they affect student and instructor interactions in online learning. It shows how AI can be used to give instant feedback on writing assignments, which gives teachers time to spend time on other things. On the other hand, the study also discusses issues about the bias and the loss of one-on-one interaction, which is vital for improving writing and critical thinking skills. The study backs up a plan in which AI helps teach but doesn’t replace human teachers.
Key Quotes
“AI can estimate which learning activity will be best suited for each student in this case, based on his/her current needs and context. This helps with personalized recommendations. This has become quite critical now, when, due to the COVID-19 pandemic, courses are being taken online and assessments are being made digitally. By analyzing a student’s current knowledge and the context in which they learn, AI can propose activities”
“These are intelligent tutoring systems performing tasks like automated grading that must be consciously integrated by course authors within the framework of online learning platforms, and not all e-learning systems use AI equally.”
“PL is, therefore, an instructional method in education, which is aimed at adapting learning to match unique needs and preferences of individual learners. Through PLSs, learners are able to choose resources and activities related to their learning style and preference”
“PL in e-learning, in its turn, will try to take advantage of the individual student profile by analyzing his or her long-term retention patterns and learning curves. This could have far-reaching consequences. For instance, the system might recommend that learners only focus their attention on the content that is relevant to their goals, and disregard all other content, such as the assignment and examination methods [61,62]. It may recommend that a student studies for examinations by repeating exercises that they already know they will later forget because it may be useful for delivering an optimal personal learning route. Doing so will promote inclusion and, more importantly, avoid discrimination against learners with special needs. This is done by accounting for individual differences in preferences and cognitive profiles [63,64,65]. Nevertheless, these ideas remain highly speculative, as current systems have not acquired such capabilities yet “
“AI teaching assistants help instructors save time answering students’ simple, repetitive questions in online discussion forums, and instead instructors can dedicate their saved time to higher-value work” (Goel & Polepeddi, 2016).
“The behavior of AI agents that do not take into account the risk of data bias or algorithmic bias can be perceived by students as discriminatory” (Crawford & Calo, 2016; Murphy, 2019).
“AI tools, such as intelligent tutoring systems (ITS), have shown a significant impact on students’ ability to improve technical skills through repeated practice and adaptive learning tailored to individual needs”
I had a tough time deciding on which article to pick. Also, the articles were pretty long, but they all had similar info, which made it easier for me to narrow things down.