“It Makes the Whole Learning Experience Better”: Student Feedback on the Use of the Interactive Whiteboard in Learning Chinese at Tertiary Level
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The widespread use of interactive whiteboards (IWB) in primary and secondary schools has been well documented, yet there is to date only limited attention to use in tertiary institutions. Macquarie University has installed this technology in many of its teaching spaces in the past few years. This paper reports a case study undertaken in the university’s undergraduate Chinese beginner course, which began to use IWB learning activities in 2009.Our study was undertaken to obtain students’ perceptions of the IWB pedagogy in Chinese language acquisition in general and in particular, of the effectiveness of IWB in the retention of Chinese characters. To many students whose first language is non-logographic, the recognition and retention of characters are the most difficult tasks in learning Chinese. Our findings indicate that the IWB’s affordance to create a variety of visual activities has impacted, most saliently, the retention of characters and syntactical elements. Students also report that the IWB has enhanced the learning experience, reflected in increased motivation and engagement through interaction with this technology. The tertiary students reveal particular learning priorities, in appreciating interaction, intellectual demand and participation, as components of effective learning. The feedback process itself proved to be useful in facilitating critical awareness in both teacher and students, of teaching strategies and learning respectively.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.000 | 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