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Record W3188479253 · doi:10.18260/1-2--36984

Discovery: Transition of an Inquiry-focused Learning Program to a Virtual Platform During the COVID-19 Pandemic (Evaluation)

2024· article· en· W3188479253 on OpenAlex
Nicolas Ivanov, Nhien Tran-Nguyen, Neal I. Callaghan, Theresa Frost, Jose L. Cadavid, Huntley H. Chang, Ileana L. Co, Patrick Diep, Guijin Li, Nancy Li, Corinna Smith, Joshua Yazbeck, Locke Davenport Huyer, Dawn M. Kilkenny

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venue2021 ASEE Virtual Annual Conference Content Access Proceedings · 2024
Typearticle
Languageen
FieldComputer Science
TopicOnline Learning and Analytics
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of TorontoAmerican Society for Engineering Education
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Transition (genetics)Computer scienceSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakData scienceVirologyMedicineChemistry

Abstract

fetched live from OpenAlex

Abstract The shift to distance learning in response to the COVID-19 pandemic has presented teachers and students with several challenges. Teachers have found themselves quickly creating distance learning materials to provide equal or greater educational opportunity and engagement as in-person instruction. This shift is met with parallel increased demand on students to independently manage their learning and coursework with the absence of in-person supervision, support, and peer interaction. In this work, we describe our approach and observations in transitioning Discovery, a secondary student science, technology, engineering, and mathematics (STEM) education program, to a virtual platform. Developed by graduate students in 2016, Discovery was designed to engage secondary students in semester-long inquiry-based projects within the context of biomedical engineering. Projects are designed to foster and reinforce critical thinking skills required for post-secondary study. Throughout the semester, students design and execute experiments within post-secondary laboratories with instructional support from both their teachers and graduate student volunteers. In response to university teaching space closures in early 2020, we developed and delivered a virtual offering of Discovery. In contrast to in-person delivery, this initial virtual offering placed greater emphasis upon quantitative analysis rather than experimental design and execution. Access to virtual laboratory simulations was provided as a substitute for in-laboratory skill development. While overall assessment of student (survey instrument) and teacher (interviews) experiences revealed a highly positive perception of the program experience, areas for improvement were also highlighted. Many students reported struggling with motivation to keep up with course materials and soft deadlines (60%) as well as the lack of guidance provided by in-person mentor and teacher interactions (50%). Teacher interviews echoed quantified student perceptions, but further identified lamentation at the loss of student-driven, open-ended, and iterative problem-solving opportunities typically afforded by Discovery. Consequently, we developed an adjusted virtual program for the Fall 2020 term. The redesigned program reintroduced the open-ended aspect of previous in-person projects, and rather than including access to commercially available virtual laboratory simulation, greater focus was placed on design of experimental procedures that were evaluated and simulated by graduate students. Additionally, greater care was taken to discretize project components and deliverable deadlines to provide enhanced structure and guidance for students. We observed this updated program structure to similar outcomes of in-person offerings. A slight majority (51.4%) of Fall 2020 students achieved higher grades for Discovery deliverables than other class assessments. In post-program surveys, ~49% of students indicated they are more likely to pursue STEM courses, ~89% would participate in the program again, and ~78% responded that the experience made them more comfortable with completing university or college level laboratory work. While these results were encouraging, comparisons to previous in-person outcomes and analysis of teacher experiences (interviews) highlighted persistent gaps in student experience while completing the program virtually.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.911
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0030.006
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.123
GPT teacher head0.371
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it