Browsing by Author "Motz, Benjamin"

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Data & experiment code for "Psychophysics in a web browser?"
de Leeuw, Joshua; Motz, Benjamin
This item contains the code files for running the experiment, the data files, and data analysis model from the article "Psychophysics in a web browser? Comparing response times collected with JavaScript and Psychophysics Toolbox in a visual search task." The article appears in the journal Behavior Research Methods.
DATA EXTACT: JOHNSON 21/22
(2022-01-07) Quick, Joshua; Johnson, Sarah; Motz, Benjamin
This item contains queries to generate data for students' interactions within Canvas course sites and Canvas modules to identify differences between students and conditions in which course content was differentially made available.
DATA EXTRACT: English Composition & Social Annotations: Hodgson21
(2021) Quick, Joshua; Hodgson, Justin; Motz, Benjamin; Israel, Jamie
The primary objective of this study is to investigate the relationship between student participation in Social Annotation (SA) and their subsequent writing practices. The secondary objective is to investigate how students participate in SA as a form of writing, social interaction, and meaning-making in multiple course contexts. The tertiary purpose of this study is to investigate how instructors plan, facilitate, and support student participation in both SA and other writing activities.This item describes the process and queries used to generate de-identified data sets of 65 Spring 2021 courses that used the Hypothes.is social annotations tool.
DATA EXTRACT: Incidence of Collaborative Tool Utilization in Canvas Course Sites for Different Disciplines
(2021) Diekman, Amanda; Motz, Benjamin; Joshi, Mansi
Past work has shown that when opportunities to work together are present within a role, students tend to report greater belonging and interest in their careers. Yet, when it comes to STEM careers vs non-STEM careers, people tend to believe that these communal opportunities are lacking. Here we are interested to understanding how subdisciplines in STEM provide these communal opportunities of working together and connecting with others. We are interested in the following question: Do STEM courses enable collaborative tools within their canvas sites? Does the use of collaborative tools differ by STEM discipline? These queries pull data from collaborative tools, and aggregates these data at the course-level, with metadata about the course level, format, and inventory.
Data Extract: Jacobson 23
(2023-04) Jacobson, Erik; Quick, Joshua; Motz, Benjamin
This entry describes queries to obtain a large number of discussion posts and corresponding metadata from Canvas discussions associated with assignments from 2018-2022. Additionally, the entry describes de-identification procedures to anonymize posters for research and privacy compliance.
Data Extract: Motz23
(2023-02-23) Motz, Benjamin; Quick, Joshua
This data extraction contains SQL script for the development of datasets on how the Boost nudging system influenced student interactions with course assessments and their performance on these assessments. Data includes assignment views, times between submission and assignment due date, assignment score, and overall course score.
DATA EXTRACT: SP20-FA20 Targeted Advising with Canvas Data Study
(2020) Quick, Joshua; Motz, Benjamin; Rust, Matthew; Gladden, James; Buyarski, Catherine
Currently at IUPUI, advising staff make periodic contact with students who are at risk for dropping out of college. At present, identification of at-risk students is inferred from student demographics, past performance, high school performance, and from flags raised by their teachers in Indiana University’s “Student Engagement Roster.” However, these measures do not reveal more timely indicators of student difficulties in their course work. Thus, the current study aims to evaluate whether the targeting of at-risk students could be augmented by including near-real-time measures of students’ behaviors in their course sites administrated via Canvas. This item describes the queries and metadata for this research project
DATA EXTRACT: Student eLearning Metrics Joined with COVID-19 Survey Responses
(2020) Motz, Benjamin; Quick, Joshua
The COVID-19 pandemic caused Indiana University, like many colleges and universities across the United States, to suspend in-person classes, transitioning fully and abruptly to online learning. This situation offered a unique opportunity to understand how the exclusive use of online education affected course instruction and student learning and behavior. To advance this understanding, the eLearning Research and Practice Lab carried out a full census survey of all Indiana University undergraduate students and instructors of undergraduate courses during Summer 2020. In the survey, some student respondents provided an affirmative Release of Academic Information information, permitting the eLearning Lab to extract information about their activity and grades within the Canvas learning management system (LMS). This item includes technical details of this data extract, and its append to the survey responses.
Going Remote: Actionable Insights from Indiana University’s Transition to Remote Instruction due to COVID-19
(2020-07) Motz, Benjamin; Jankowski, Harmony; Snapp-Childs, Winona; Quick, Joshua
On March 10, 2020, Indiana University (IU) announced the suspension of in-person instruction due to COVID-19. At that time, the eLearning Research and Practice Lab, a laboratory within the Indiana University Pervasive Technology Institute, began preparing to conduct a full-census survey of all undergraduates and instructors across all IU campuses. The study’s purpose was to examine student and instructor experiences of the transition to remote instruction, and to identify actionable insights that may improve instruction during future semesters. This report was prepared and distributed internally at IU, in order to provide rapid evidence-based recommendations for instructional practice.