Bibliographic record
Abstract
To date, legal education in Hong Kong is still mainly carried out through teacherdesigned classes: law teachers are the ones selecting and preparing course materials whereas students as recipients are assessed through written examinations.Speaking from a student's perspective, I (Phoebe) feel that following this format, students learn passively.Most of the time, they stay quiet and jot down what their teachers say.There are, of course, innovative alternatives, such as flipped classrooms and experiential learning, but these are still invariably designed by teachers.Despite the growing awareness and adoption of student-teacher partnership in other disciplines, legal education has been slow in responding to this call.As a teacher, I (Alice) observe that many colleagues regard course design as the teacher's exclusive jurisdiction.When they try out innovative technology for learning, for example, they will enlist technical staff or invest in new hardware or software.From my own experience, successful pedagogical innovation depends much on understanding and meeting students' needs, and we can do so by involving students as partners and co-designers.In this reflective piece, we (a law student and a law teacher) reflect on our experiences of initiating and engaging in a learning and assessment activity called in-class optional niche, or ICON in short.We will share how students have been empowered and incentivised to co-create learning and teaching materials and collaborate with their teacher and peers in the teaching process.Our aim is to show that student-teacher partnership in legal education is not only viable, but also beneficial to both students and teachers.We hope the entrenched expert-novice divide could be bridged by "a collaborative, reciprocal process through which all participants have the opportunity to contribute equally, although not necessarily in the same ways, to curricular or pedagogical conceptualisation, decisionmaking, implementation, investigation, or analysis" (Cook-Sather et al., 2014, pp.6-7) with an emphasis on decision-making. IN-CLASS OPTIONAL NICHE (ICON)ICON is a learning and assessment activity in an intellectual property law elective.The course is offered to final-year students in four undergraduate programmes at the University of Hong Kong and delivered through 12 weekly seminars in one semester.ICON is optional as it is meant to invite (rather than require) students to share the teaching and learning of the course.While other assessment components of the course, namely an optional research essay and a compulsory written examination, test students' ability to analyse legal problems and present their arguments in writing, ICON aims at raising
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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".