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"It is not the possession of knowledge, of irrefutable truth, that makes the man of science, but the persistent and restless search for truth."Karl Popper

Paper design KTH - Lombardi

  • Importance of research skills for STEM students highlighted across Europe (Joyce, 2014; Blin, 2010; Zavalevskyi, 2023; Filippi, 2017).
  • Research skills crucial for knowledge-based economy and society, fostering innovation and new knowledge. Cultivation of research skills is a key learning outcome, STEM education methodologies can contribute significantly (Blin, 2010; Zavalevskyi, 2023).
  • Inquiry-based science education activities enhance interest in STEM careers and introduce responsible research and innovation practices (Filippi, 2017).
  • AI, specifically ChatGPT, can enhance students’ research capabilities (Kumar, 2019; Suparyati, 2023).
  • AI tools like logic, classifiers, and machine learning methods can be used in student modeling for research competencies development (Drigas, 2009).
  • AI applications like personalized learning experiences and chatbots can support research skills development, especially for international students in higher education (Wang, 2023).

Literature & Research Question

"How is the implementation of Artificial Intelligence in research activities perceived by undergraduate students in STEM disciplines?"

For these reasons, this study aims to ascertain how the implementation of AI in research activities is perceived by students of an undergraduate track in STEM, and its RQ1 is:

  • AI shows potential in enhancing students’ research skills, but research on students’ perceived effectiveness of AI is lacking. Chichekian (2022) emphasizes the need for complementary research projects to effectively integrate AI tools in education.
  • Almaraz-López (2023) and Uma (2023) highlight students’ awareness of AI’s impact and their willingness to deepen their AI education, but also note the need for expanded and improved AI education.
  • Rizvi (2023) discusses AI’s potential in increasing student motivation, but also stresses the importance of addressing ethical issues.
  • These studies collectively underline the need for further research on students’ perceptions of AI’s effectiveness in acquiring research skills.

Literature & Research Question

Inquiry-based learning experiment with Gemini for engineering students: Objectives: To evaluate the impact of AI on student learning and research in an Inquiry-based learning context. Phases: 1. Problem definition and group formation - Lecturers and students define global engineering challenges to be explored and specific research questions. Students are randomly assigned to an experimental or control group. 2. Familiarization with Gemini - Experimental group: Introduction to Gemini and its capabilities for Inquiry-based learning. Tutorials and workshops for using the system. Control group: Introduction to Inquiry-based learning with traditional resources and methodologies. 3. Research and Analysis - Experimental group: Formulation of Gemini-specific queries and analysis of results. Control group: Research conducted with traditional methodologies (bibliographies, databases, etc.). 4. Processing and presentation of results - Both groups: Synthesis of information gathered, formulation of conclusions and reflections on the experience. Presentation of results and discussion. 5. Evaluation and feedback - Questionnaires: Administration of questionnaires to both groups to assess perceptions, learning, satisfaction and research experience. Data analysis: Comparison of results between the two groups to determine the impact of Gemini.

Methods

Phase 1 - Data analysis Experimental group: Analysis of results obtained from Gemini for the research question. Identification of significant patterns, trends and relationships in the data. Comparison of the results with the hypotheses formulated in the design phase. Control group: Analysis of data collected using traditional methodologies. Comparison of results with those of the experimental group. Phase 2 - Interpretation of results: Discussion of the meanings that emerged from the data analysis. Interpretation of differences (if any) between the two groups. Evaluation of the impact of Gemini on student learning and research. Identification of the strengths and weaknesses of using Gemini. Phase 3 - Drafting the Results and Discussion section. Presentation of data in a clear and concise manner, using tables, graphs and figures. Discussion of the results in relation to the research questions and hypotheses formulated. Interpretation of results in a critical and reflective manner.Formulation of conclusions supported by the data. Identification of implications for teaching practice and future research.

Results & Discussion

Almaraz-López, C., Almaraz-Menéndez, F., & López-Esteban, C. (2023). Comparative Study of the Attitudes and Perceptions of University Students in Business Administration and Management and in Education toward Artificial Intelligence. Education Sciences. Blin, F., & Wickham, S. (2010). DEVELOPING RESEARCH SKILLS AMONG UNDERGRADUATE STUDENTS: CASE STUDIES FROM THE HUMANITIES AND SCIENCES AT DUBLIN CITY UNIVERSITY. Chichekian, T., & Benteux, B. (2022). The potential of learning with (and not from) artificial intelligence in education. Frontiers in Artificial Intelligence, 5. Filippi, A., & Agarwal, D. (2017). Teachers from Instructors to Designers of Inquiry-Based Science, Technology, Engineering, and Mathematics Education: How Effective Inquiry-Based Science Education Implementation Can Result in Innovative Teachers and Students. Science education international, 28, 258-270. Joyce, A. (2014). Stimulating interest in STEM careers among students in Europe: supporting career choice and giving a more realistic view of STEM at work. Rizvi, S. (2023). Revolutionizing Student Engagement: Artificial Intelligence’s Impact on Specialized Learning Motivation. International Journal of Advanced Engineering Research and Science. Uma, D.R. (2023). An Analysis of the Effectiveness of AI in Education with a Focus on College Students. Journal of Development Economics and Management Research Studies. Zavalevskyi, Y., Gorbenko, S., & Vasylenko, I. (2023). Formation of Students' Readiness for Research Activities in the Context of STEM-Education. Problems of Education.

References