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
Purpose In this paper, the challenging and thorny issue of assessing graduate attributes (GAs) is addressed. An interdisciplinary team at The University of Alberta ----developed a formative model of assessment centered on students and instructor interaction with course content. Design/methodology/approach The paper starts by laying the theoretical groundwork on which this novel GA assessment tool is based, that is, competency-based education, assessment theory and GA assessment. It follows with a description of the online assessment tool for GAs that was developed in the course of this project. Findings The online assessment tool for GAs targets three types of stakeholders: (1) students, who self-assess in terms of GAs, (2) instructors, who use the tool to define the extent to which each GA should be inculcated in their course and (3) administrators, who receive aggregate reports based on the data gathered by the system for high-level analysis and decision-making. Collected data by students and professors advance formative assessment of these transversal skills and assist administration in ensuring the GAs are addressed in academic programs. Graduate attributes assessment program (GAAP) is also a space for students to build a personal portfolio that would be beneficial to highlight their skills for potential employers. Research limitations/implications This research has strong implications for the universities, since it can help institutions, academics and students achieve better results in their practices. This is done by demonstrating strong links between theory and practice. Although this tool has only been used within the university setting by students, instructors and administrators (for self-, course and teaching and program improvement), it could increase its social and practical impact by involving potential employers and increase our understanding of student employability. Moreover, because the tool collects data on a continuous basis, it lends itself to many possible applications in educational data mining, Practical implications The GAAP can be used and adapted to various educational contexts. The plugin can be added to any Learning Management System (LMS), and students can have access to their data and results throughout their education. Social implications The GAAP allows institutions to provide a longitudinal formative assessment of students’ graduate attributes acquisition. It provides solid and valid evidence of students’ progress in a way that would advance society and citizenship. Originality/value To date, the GAAP is the first online interactive platform that has been developed to longitudinally assess the acquisition of GAs during a complete academic cycle/cohort. It provides a unique space where students and instructors interact with assessment scales and with concrete data for a complete university experience profile.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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