Electronic student portfolios: documenting learning in grade 2/3
Bibliographic record
Abstract
Capturing, documenting, assessing, and highlighting the dynamic nature of learning has challenged educators for decades.Student portfolios offer flexible and versatile options in meeting these goals.Rapid advances in technology have permitted and indeed, enticed educators in the exploration of electronic portfolios.Technology such as computers, scanners, digital cameras, CD writers, and the World Wide Web have expanded the possibilities in documenting student growth and learning.My qualitative study focuses on using electronic portfolios in my grade 2/3 class at Blackie School.Four students were selected to participate, with equal representation from males, females, grade 2, and grade 3. The participants compiled electronic portfolios to document their learning and growth throughout the school's second reporting period.The creation of the electronic portfolios took place over a six-week period in March and April 2001.Data was collected from my journal, observations, studentjoumals, student surveys, and parent surveys.From the data, two general conclusions emerged.Firstly, an electronic showcase portfolio or an electronic component within the traditional paper portfolio, may be more viable options for Division I (K-3) students.The time and challenges encountered in digitizing the volumes of paper samples necessary for an electronic process portfolio were enormous.Secondly, a robust computer network including a fileserver and peripherals are essential, as is technological support and training for educators.The computer system must be able to support the daily demands of the general school popUlation in addition to supporting massive multimedia files created by electronic portfolios.Indeed, technology can be incorporated into student portfolios, offering new avenues in documenting student IV learning and growth.However, the extent and role oftechnology must be examined.This study revealed that, given the current setting at Blackie School, creating completely electronic student process portfolios for a full class of Division I students would not be a viable alternative at this time.This study documents our experiences with creating electronic student portfolios in grade 2/3.I hope that it will be of some assistance to other Division I educators in exploring and determining the role of technology in documenting student learning.v Preface "The teacher is no longer merely the-one-who-teaches but one who is himselftaught in dialogue with the students, who in turn while being taught also teach.They become jointly responsible for a process in which all grow."Paulo Freire in Pedagogy of the Oppressed VI
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".