AI Course Design Planning Framework: Developing Domain-Specific AI Education Courses
Abstract
:1. Introduction
- RQ1: How do instructors perceive the usability and user experience of the course planning framework as an instrument to structure and develop domain-specific AI courses?
- RQ2: What aspects of the framework could be improved to enhance its usability and user experience?
2. Related Work
2.1. AI Education
2.2. Interdisciplinary Teaching in Higher Education
2.3. Course Planning Frameworks
3. AI Course Design Planning Framework
3.1. AI in the Domain
3.1.1. Domain
3.1.2. Potential AI Use Cases in the Domain
3.1.3. Data in the Domain
3.1.4. Implications of Using AI in the Domain
3.1.5. Additional Learning Resources
3.2. Learning Environment
3.2.1. Learners and Their Interaction with AI
3.2.2. Instructors
3.2.3. Internal Support
3.3. Course Implementation
3.3.1. Learning Outcomes
3.3.2. Assessment
3.3.3. Learning Activities
3.4. Intended Use of the AI Course Design Planning Framework
4. Methods
4.1. Design-Based Research
4.2. Procedure
4.2.1. Evaluation Instruments
4.2.2. Data Analysis
5. Results
5.1. Participants
5.2. Usability (RQ1)
5.3. User Experience (RQ1)
5.4. Qualitative Responses (RQ2)
6. Discussion
6.1. Discussion of the Results
6.2. Limitations
6.3. Strengths and Implications
7. Conclusions and Outlook
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
AI | Artificial Intelligence |
CI | Confidence Interval |
CS | Computer Science |
ESCO | European Skills/Competencies, Qualifications and Occupations |
MOOC | Massive Open Online Course |
OER | Open Educational Resources |
RQ | Research Question |
SD | Standard Deviation |
SMART | Specific, Measurable, Achievable, Relevant and Time-Bound |
SUS | System Usability Scale |
UEQ | User Experience Questionnaire |
Appendix A
Type of Change | Modification |
---|---|
Design and Layout | 1. Changing the order of pillars to reflect the order in which they should be filled |
2. Numbering the pillars | |
3. Improving readability through different coloring | |
Clarity and Usability | 1. Renaming the pillars and the categories |
2. Adding additional category of domain | |
3. Improving the clarity of the guiding questions in each category |
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SUS-Item | Mean | SD | Range |
---|---|---|---|
I found the system unnecessarily complex. (−) | 2.0 | 1.1 | 4 |
I thought the system was easy to use. | 4.3 | 0.4 | 1 |
I thought there was too much inconsistency in this system. (−) | 1.9 | 0.8 | 2 |
I would imagine that most people would learn to use this system very quickly. | 4.7 | 0.5 | 1 |
I found the system very cumbersome to use. (−) | 1.8 | 0.9 | 3 |
I felt very confident using the system. | 3.9 | 0.6 | 2 |
I needed to learn a lot of things before I could get going with this system. (−) | 1.4 | 0.6 | 2 |
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Schleiss, J.; Laupichler, M.C.; Raupach, T.; Stober, S. AI Course Design Planning Framework: Developing Domain-Specific AI Education Courses. Educ. Sci. 2023, 13, 954. https://doi.org/10.3390/educsci13090954
Schleiss J, Laupichler MC, Raupach T, Stober S. AI Course Design Planning Framework: Developing Domain-Specific AI Education Courses. Education Sciences. 2023; 13(9):954. https://doi.org/10.3390/educsci13090954
Chicago/Turabian StyleSchleiss, Johannes, Matthias Carl Laupichler, Tobias Raupach, and Sebastian Stober. 2023. "AI Course Design Planning Framework: Developing Domain-Specific AI Education Courses" Education Sciences 13, no. 9: 954. https://doi.org/10.3390/educsci13090954
APA StyleSchleiss, J., Laupichler, M. C., Raupach, T., & Stober, S. (2023). AI Course Design Planning Framework: Developing Domain-Specific AI Education Courses. Education Sciences, 13(9), 954. https://doi.org/10.3390/educsci13090954