Teaching Undergraduate Students to Create and Use Concept Maps to Improve Their Learning
Why this work is in the frame
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Bibliographic record
Abstract
The use of concept maps have been shown to be a more effective study method, however students report that they rarely adopt this practice and resort to highlighting and rereading their notes. It is possible that students are intimidated to attempt new, unfamiliar strategies and that with some training, they may be more likely to employ better methods. The purpose of this study was to assess if we could modify student study behaviours through modelling various active learning strategies throughout the year, including concept mapping. As part of this study, students in our first and second year undergraduate human physiology courses were invited to participate. These courses had mandatory tutorials each week where students worked in small groups that we had assigned. During the year, different types of active learning methods were introduced. Among these, two tutorials were designed to model the use of concept mapping. In the first semester, students were given a partially constructed concept map on skeletal muscle physiology to demonstrate how concept maps can be used to connect material they learned in class. In the second semester, the students were given a list of terms and concepts related to renal physiology and were asked to construct their own maps. In our first tutorial, we surveyed students to determine the learning strategies they currently employed using a modified strategies for learning questionnaire (pre‐MSLQ). Participants used a 7 point Likert scale to answer the 30 item survey, with a value of 1 indicating a strong disagreement to the statement and 7 reported for strongly agreeing. Again at the end of the year, students were asked to complete the same modified strategies for learning questionnaire (post‐MSLQ). We compared this to the pre‐MSLQ to determine if their methods used to approach studying course material had changed with regards to the learning activities, including concept mapping. Additionally, at the end of the year, students were asked to complete a learning attitudes survey, which evaluated the students’ perceptions of learning achieved with the use of these learning techniques modelled in their tutorial times. When comparing the pre and post‐MSLQ surveys, participants reported a score of 4.6 in the pre‐course survey, but an increased score of 5.4 in the post‐course survey (p<0.01, paired t‐test) to the statement “When I am studying a topic, I try to make everything fit together into a “big picture” (ie. charts, concept maps). In the learning attitudes survey, preliminary data from the statement “I feel I learned more when I used concept maps in the learning process than when I used my usual study techniques”, 60% of students reported that they agreed with this statement. Meanwhile, 70% of participants agreed with the statement, “I hope to employ concept maps in future learning activities”, suggesting that they found the activity beneficial. In follow up studies, we hope to determine the quality of created concept maps and analyze if this correlated to differences in participants performances on evaluations in the course. Since participants also reported an increase in the use of other active learning techniques, such as peer teaching, we also plan to explore whether these adopted techniques may contribute to any observed improvements in course evaluations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it