WIP: Exploratory Learning Before Instruction on Python Error Messages: Looking Beyond the Learning Outcomes
This research work in progress research paper examines student perceptions after completing an exploratory learning lesson before instruction on an introductory programming concept. During exploratory learning activities, students explore a novel concept prior to instruction-the reverse of typical instruct-then-practice methods. Exploratory learning before instruction can help students activate prior knowledge, become aware of their knowledge gaps, and discern important problem features to improve conceptual understanding. Students in a first-year engineering course (N=402) learned about Python error messages in one of two conditions. In the explore-first condition, students completed a collaborative activity prior to instruction. In the instruct-first condition, students received instruction prior to the activity. Following the activity and instruction, students completed a survey to assess their perceptions of the activities. Survey items (e.g. cognitive load, self-efficacy, belonging, knowledge gaps) were chosen as potential factors that could explain learning outcomes between the two conditions. In prior work, we found higher posttest scores in the instruct-first compared to explore-first condition, contrary to the majority of previous studies. Cognitive load and knowledge gaps were higher in the explore-first condition than the instruct-first condition. Self-efficacy and competence were lower in the explore-first condition. No other significant differences were found. Exploring before instruction might disrupt learning and perceived efficacy and competence if the activity is too challenging, or if the instruction does not fully resolve gaps in students' knowledge.
Authors
- Campbell R. Bego (ORCID: https://orcid.org/0000-0002-8125-3178)
- Angela Thompson (ORCID: https://orcid.org/0000-0002-7605-7690)
- Marci S. DeCaro (ORCID: https://orcid.org/0000-0001-6753-0725)
- Cenetria Crockett
- Lianda Velić
Institutions
- University of Louisville (US)
Publication Details
- Published
- 2024-10-13
- DOI
- https://doi.org/10.1109/fie61694.2024.10893012
- Citations
- 1
- Primary Topic
- Online Learning and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 0.41