Scaling-up Collaborative Learning for Large Introductory Courses Using Active Learning Spaces, TA training, and Computerized Team Management

Essick, Ray; West, Matthew; Silva, Mariana; Herman, Geoffrey L.; Mercier, Emma

doi:10.18260/p.27342

Cited by 7 publications

(6 citation statements)

References 31 publications

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“…Importantly, the use of computer-based assessment does not preclude having assessments that are not autogradeable in a course; in fact, the use of computer-based testing, where appropriate, can free faculty's/course staff's time to include more tasks that benefit from expert input (e.g., projects, lab reports, etc.) in the course (Essick, West, Silva, Herman, & Mercier, 2016;Sanders, West, & Herman, 2016;West, Silva-Sohn, & Herman, 2015).…”

Section: Introductionmentioning

confidence: 99%

Analyzing the decline of student scores over time in self‐scheduled asynchronous exams

Chen

West

Zilles

2019

J of Engineering Edu

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Background When students are given a choice of when to take an exam in engineering and computing courses, it has been previously observed that average exam scores generally decline over the exam period. This trend may have implications both for the design of interventions to improve student learning and for data analysis to detect collaborative cheating. Purpose/Hypothesis We hypothesize that average exam scores decline over the exam period primarily due to self‐selection effects, where weaker students tend to choose exam times later in the exam period, while stronger students are more likely to choose earlier times. Design/Method We collected 31,673 exam records over four semesters from six undergraduate engineering and computing courses that had both synchronous exams (all students at the same time) and asynchronous exams (students choose a time). We analyzed student exam time choice and asynchronous exam scores, using synchronous exam scores in the same course as a control variable. Results We find that students with lower scores on synchronous exams generally elect to take asynchronous exams later and that controlling for student ability (via synchronous exams) removes 70% of the decline observed in average asynchronous exam scores over the exam period but does not eliminate the downward trend with time. Conclusions We conclude that self‐selection effects are primarily responsible for exam score declines over time, that exam time selection is unlikely to be a useful target for interventions to improve performance, and that there is no evidence for widespread collaborative cheating in the dataset used in this research.

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Section: Introductionmentioning

confidence: 99%

Analyzing the decline of student scores over time in self‐scheduled asynchronous exams

Chen

West

Zilles

2019

J of Engineering Edu

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“…During the implementation phase, we found that the TAs and CAs differed in the way they used the orchestration tool and the value they perceived in the tool. Differential uptake and use of orchestration tools by teachers have been reported elsewhere [36] indicating that teaching experience and comfort with technology may influence their uptake of a tool.…”

Section: Discussionmentioning

confidence: 84%

“…As described above, the designers of collaborative TEL tools must reflect on the teacher's knowledge of implementing collaboration [36]. Our orchestration tool was built in collaboration with engineering faculty and TAs; however, we also used insight from expert teachers and prior research, not only to support TAs in the classroom but to simultaneously teach them about collaboration.…”

Section: Study Contextmentioning

confidence: 99%

Co-Design of an Orchestration Tool: Supporting Engineering Teaching Assistants as they Facilitate Collaborative Learning

Lawrence¹,

Mercier²

2019

IxD&A

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This paper describesa design-based implementation research (DBIR) project, focused on the co-design and implementation of an orchestration tool for teaching assistants (TAs) in required engineering classes. Building on our collaboration with the engineering department, we identified a need for a tool that provides insight into groups to help TAs intervene in real-time. This paper presents two phases of our iterative co-design process. The first phase includes the initial design of the tool from design workshops with TAs. The second phase focuses on a 16-week implementation of the orchestration tool and reports on interviews with TAs to understand how they used the tool. Findings indicate that the impact of the tool varies and that the uptake of the tool differs by TA. Finally, we reflect on the co-design process and discuss future directions for the creation of this technology.

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“…There are many different models for training teaching assistants [24]. The vast majority of training models tend to be single-day workshops [25], but others use week-long workshops [26], weekly courses [27], periodic training videos [28], or multiple multi-phased sessions [24], [29], [30]. These training sections are often interactive, including opportunities for discussions and group exercises [31].…”

Section: Introductionmentioning

confidence: 99%

Efforts to Improve Undergraduate Grader Consistency: A Qualitative Analysis

Hicks

Douglas

2018 ASEE Annual Conference &Amp; Exposition Proceedings

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Scaling-up Collaborative Learning for Large Introductory Courses Using Active Learning Spaces, TA training, and Computerized Team Management

Cited by 7 publications

References 31 publications

Analyzing the decline of student scores over time in self‐scheduled asynchronous exams

Analyzing the decline of student scores over time in self‐scheduled asynchronous exams

Co-Design of an Orchestration Tool: Supporting Engineering Teaching Assistants as they Facilitate Collaborative Learning

Efforts to Improve Undergraduate Grader Consistency: A Qualitative Analysis

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