How students leverage assignment submission flexibility — a case study.
Description
Raw data used for generating each corresponding figure from the manuscript entitled "How students leverage assignment submission flexibility — a case study." Manuscript Abstract: Recent pedagogical trends in post-secondary education focus on how providing students with greater autonomy through assignment submission flexibility offers benefits ranging from increased learning to stress reduction. Unfortunately, the relationship between submission flexibility and any specific benefit is not firmly established. One explanation for this is a potential misalignment between anticipated benefits and an understanding of how most students leverage extended opportunities for assignment completion. The goal of this study was to investigate the relationship between assignment submission flexibility and how students used the opportunity. Quantitative evidence reveals that most students routinely maximized the time taken before submitting assignments. This occurred independent of assignment type, teaching modality, or the duration assignment availability. The results support a conclusion that most students do not capitalize on increased flexibility to meet the demands of their unique schedules. Instead, they appear to adapt their schedules to submit assignments shortly before a perceived deadline. Calculations: Elapsed opportunity window — Filemaker was used to calculate an elapsed opportunity window (EOW) for each assignment type. To do so, the difference between the assignment submission and the due timestamps was divided by the difference between the availability and due timestamps. Filemaker was then used to format and export data for histogram generation using ggplot2 (https://ggplot2.tidyverse.org/), a data visualization package for the open source R programming language (https://www.r-project.org/). All statistical analysis was performed with rstatix (https://cran.r-project.org/web/packages/rstatix/index.html), a framework for basic statistical tests.
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All assignment data was collected using the Canvas LMS REST API for Quiz Submissions (https://canvas.instructure.com/doc/api/quiz_submissions.html). These datasets included information related to each assignment type (practice questions, quiz, or exam) and the time of submission. Course activity data were collected from the Canvas LMS using the New Analytics reports and course activity features. Video access activity was obtained through Kaltura using the LTI-based integration with Canvas by downloading ‘User Engagement’ data. Downloaded datasets were then automatically parsed to capture content type and access time before import into a Filemaker (https://www.claris.com/) database for storage and further analysis. In total, assignment and activity data was collected from two in-person and 5 online sections of a Introductory Cell Biology course between the Springs of 2021-2023.