Achieving greater academic success: engaging students by providing feedback and summative grades for note taking
Bibliographic record
Abstract
This mixed method research project addressed the question, "Will the awarding of grades for note taking increase the average final grades of students enrolled in a first semester college English course?"Four sections of the same EN1201, English Composition course, participated in this research project.Two sections of four were required to take daily class notes in Learning Journals, which were graded at mid-semester and at end of the semester and earned students up to ten percent of their final grade.The other two sections were able to earn up to ten percent of their final grade.for writing two 300-word Learning Summaries of the course content that were graded at mid-semester and also at the end of the semester.The average final grades of the two groups were compared.In addition, qualitative research methods were used to record the responses by the two groups on a pretest and post-test Student Learning Survey.The students who kept daily Learning Journals were expected to achieve a higher average final grades than students who wrote Learning Summaries.However, because of the number of uncontrolled variables in this research project, final grade differences between these two groups were not statistically significant.The data from this research failed to reject the null hypothesis which stated that there was no correlation between daily note taking and higher final grades.Therefore, more research with greater control of the variables is recommended. GLOSSARYFor the purpose of this research project, the following terms are defined.1. Formative Feedback-written or oral comments that guided and reinforced students' writing included in learning summaries or note taking 2. Lecture-orally delivered instruction to a class of post-secondary students 3. Learning Journal-daily notes of class of college lectures organized in a binder and submitted at mid-term and during the last week of class ,worth up to ten grade points and defined in the EN 1201 course outlines.4. Learning Summary-two three-hundred word reviews of college and university course content submitted at mid-term and during the last week of class, worth up to ten grade points and defined in the EN1201 course outlines.5. Student Learning Survey-a pretest and post test questionnaire to assess students' basic demographics, expectations and appreciation of the value of note taking 6.Summative Feedback-the final grade earned by students at the end of a semester of EN1201 v Achieving Greater Academic Success: Engaging Students by Providing Formative Feedback and Summative Grades for Note Taking Chapter 1
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.030 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".