Literature Review Assignment Instructions

Track: Literature Review Track

Format: IEEE

Maximum Length: 5000 words (excluding title page, references, and appendices)

Overview

This project will be focused on the Literature Review track.

Please use the research question and references listed below for the literature review for the paper.

This assignment must strictly follow the guidelines provided in the uploaded instructions.pdf, including all sections/questions and formatting expectations.

The literature review must be grounded in cognitive science concepts, models, and theories discussed in the course. Use Introduction to Cognitive Science by Paul Thagard to reference and integrate course concepts.

Research Question Below:

A. Broad Topic Area

The broad topic this project examines is how AI chatbots support cognitive processes and learning during academic tasks in higher education. It focuses on the role of AI chatbots tools as learning aids and how they influence students thinking, mental effort, and problem solving while studying.

B. Research question

How do AI chatbots support students cognitive processes during academic tasks, particularly by reducing cognitive load, and how does this influence problem solving performance and learning outcomes in higher education?

References

[1] H. Liu, X. Zhang, J. Zhou, Y. Shou, Y. Yin, and C. Chai, “Cognitive styles and design performances in conceptual design collaboration with GenAI,” International Journal of Technology and Design Education, vol. 35, no. 3, pp. 11691202, 2025, doi: 10.1007/s10798-024-09937-y.

[2] W. Sun and J. Liu, “The Impact of Human-AI Interaction Patterns on Problem Solving, AI Literacy, and Metacognition,” International Conference on AI Research, vol. 5, no. 1, pp. 587596, 2025, doi: 10.34190/icair.5.1.4276.

[3] S. Feng, “Group interaction patterns in generative AIsupported collaborative problem solving: Network analysis of the interactions among students and a GAI chatbot,” British Journal of Educational Technology, vol. 56, no. 5, pp. 21252145, 2025, doi: 10.1111/bjet.13611.

[4] J. L. Heyman, S. R. Rick, G. Giacomelli, H. Wen, R. J. Laubacher, N. Taubenslag, M. S. Knicker, Y. Jeddi, P. Ragupathy, J. Curhan, and T. W. Malone, “Supermind Ideator: How scaffolding Human-AI collaboration can increase creativity,” Collective Intelligence, vol. 3, no. 4, 2024, doi: 10.1177/26339137241305117.

[5] C. Hou, G. Zhu, and V. Sudarshan, “The role of critical thinking on undergraduates reliance behaviours on generative AI in problemsolving,” British Journal of Educational Technology, vol. 56, no. 5, pp. 19191941, 2025, doi: 10.1111/bjet.13613.

[6] M. Urban, J. Lukavsk, C. Brom, V. Hein, F. Svacha, F. Dchtrenko, and K. Urban, “Prompting for creative problem-solving: A process-mining study,” Learning and Instruction, vol. 99, Art. no. 102156, 2025, doi: 10.1016/j.learninstruc.2025.102156.

[7] Y. Hwang and J. H. Lee, “Exploring students experiences and perceptions of human-AI collaboration in digital content making,” International Journal of Educational Technology in Higher Education, vol. 22, no. 1, Art. no. 44, 2025, doi: 10.1186/s41239-025-00542-0.

[8] C. Hou, G. Zhu, V. Sudarshan, F. S. Lim, and Y. S. Ong, “Measuring undergraduate students reliance on Generative AI during problem-solving: Scale development and validation,” Computers and Education, vol. 234, Art. no. 105329, 2025, doi: 10.1016/j.compedu.2025.105329.

[9] N. Law, N. Wang, M. Ma, Z. Liu, L. Lei, S. Feng, X. Hu, and J. Tsao, “The role of generative AI in collaborative problemsolving of authentic challenges,” British Journal of Educational Technology, 2025, doi: 10.1111/bjet.70010.

[10] D. Siemon, E. Elshan, T. de Vreede, P. Ebel, and G. de Vreede, “Beyond anthropomorphism: Social presence in humanAI collaboration processes,” Journal of Management Studies, 2025, doi: 10.1111/joms.70000.

[11] P. Thagard, Mind: Introduction to Cognitive Science, 2nd ed. Cambridge, MA, USA: MIT Press, 2005.