Electronic Portfolio: Reflective Project in a Community of Language Learners
Bibliographic record
Abstract
In this article, I present my stance as an English as a second language (ESL) practitioner resulting from empirical observations of the development of eportfolio reflective projects by five groups of approximately 10-20 intermediate-level language learners in an online learning community during five iterations of the same course (February 2018-June 2020). I provide an insight into the experiences of ESL students with their first eportfolios as a capstone project based on ongoing observations grounded on theoretical concepts of the affective domain and a more ecological aspect of constructivism. The first four groups of 10-20 students completed their program of studies in a blended format – three days onsite and two online. The fifth group with 20 students, however, due to COVID-19, was thrust into learning entirely at a distance prior to the completion of their second module. In each cohort, students were aware of the remaining modules in their program of studies and waited in anticipation – and some form of trepidation – for their reflective project. The capstone eportfolio project was the fifth and final module in a five-month program of studies where students chose a platform for their projects (technology) and populated the pages with learning episodes (pedagogy) experienced in the previous four modules. These eportfolio projects, developed by the students individually and in collaboration with their peers, fostered engagement and feedback interaction at various stages. While developing their reflective projects, students learned to leverage eportfolio technology to enhance the achievement of their goals as well as eportfolio pedagogy to articulate the attainment of competencies. Since evidence of core competencies in each language skill ability is a program requirement, modules preceding the creation of eportfolios necessitate tasks that foster learner awareness related to language skills, abilities, and attitudes. Although students eventually understand what the competencies are, they often grapple with how they are attained, and why they are required. As reflective projects grounded on academic rigour and underpinned by theoretical principles, these eportfolios espouse self-awareness and deeper learning. As such, they foster student agency and empower creators to articulate their experiences as they reflect on the learning to date. My observations of five groups of language learners developing their first eporfolio as a capstone project may help inform the field of online pedagogy and also contribute toward a better understanding of eportfolios as reflective projects in blended and online learning communities.
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.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 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".