Portfolio Project as Summative Language Assessment: Engaging Learners Online
Bibliographic record
Abstract
High stakes midcourse and final exams have long been a dominant assessment model. But exam performance does not necessarily correlate with learning or students’ ability to apply learning to real-life scenarios outside the classroom. Reliance on such high-stakes assessments can result in elevated learner stress during exam times and lack of learner engagement during non-exam times. In contrast, active learning requires ongoing student engagement, and assessments of student work completed in such activities are authentic archetypes of student learning that demonstrate student ability to apply their learning to authentic situations, problems, and issues. This article argues that assessment practices based on multiple, low-stakes, iterative assessments within an active learning environment provides more feedback and engages students in their own learning as active participants, which leads to increased student success. The case study presented in this article is specific to foreign language courses offered through online education. Combining best practices of learner engagement in the online environment and assessment in the communicative language classroom, language faculty in an open enrollment program developed an assessment model for asynchronous, introductory language courses in the online environment that relies on multiple low-stakes assessments that culminate in a final, summative portfolio project. This article will offer examples of how the portfolio project is situated in the course and an overview of portfolio project topics. Example instructions and assessment rubrics will be provided. Data from the first full year of implementation will be analyzed to begin to assess the impact and effectiveness of this portfolio assessment. Resume : Placer les examens importants en milieu et fin de cours constitue depuis longtemps un modele d'evaluation dominant. Mais les resultats aux examens ne sont pas necessairement lies a l'apprentissage ou a la capacite des etudiants a appliquer leurs apprentissages a des scenarios de la vie reelle a l'exterieur de la classe. Le recours a de telles evaluations, dont les enjeux sont eleves, peut entrainer un stress eleve chez l'apprenant pendant les periodes d'examen et un manque d'engagement de la part de l'apprenant pendant les periodes ou il n'y a pas d'examen. L'apprentissage actif exige un engagement continu de la part des etudiants, et des evaluations portant sur des activites faisant ressortir leur capacite a appliquer leurs apprentissages a des situations, problemes et enjeux authentiques. Cet article defend l’idee que les pratiques d'evaluation fondees sur des evaluations multiples et iteratives a faibles enjeux, dans le cadre d’un apprentissage actif, fournissent une retroaction plus ciblee et favorisent l’engagement des etudiants dans leur propre apprentissage en tant que participants actifs, ce qui favorise leur reussite. L'etude de cas presentee dans cet article est centree sur les cours de langues etrangeres offerts en ligne. Dans un programme de formation ouverte, les professeurs de langue ont combine les meilleures pratiques d'engagement de l'apprenant dans l'environnement en ligne et l'evaluation en classe de communication en langue etrangere afin de developper un modele d'evaluation pour des cours asynchrones d'introduction a la langue. Celui-ci repose sur de multiples evaluations a faibles enjeux qui aboutissent au projet final de portfolio d’evaluation sommative. Cet article donnera des exemples de la facon dont le projet de portfolio se situe dans le cours et offrira un apercu des sujets associes au projet de portfolio. Des exemples d'instructions et de rubriques d'evaluation seront proposes. Les donnees de la premiere annee complete de mise en œuvre seront analysees pour commencer a evaluer l'impact et l'efficacite de ce portfolio d’evaluation. Mots-cles : evaluation sommative, cours de langue en ligne, conception de cours, projets de portfolio
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How this classification was reachedexpand
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 | 0.002 | 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 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".