How CS1 Students Experienced COVID-19 In the Moment: Using An Experience Sampling Approach to Understand the Transition to Emergency Remote Instruction
Title: How CS1 Students Experienced COVID-19 In the Moment: Using An Experience Sampling Approach to Understand the Transition to Emergency Remote Instruction
While computer science (CS) education researchers have frequently examined what happens in courses, programs of study, or occupations in general, they have less frequently addressed finer-grained experiences that spark students' interest in CS. One excellent way to study these types of student experiences is the Experience Sampling Method (ESM). ESM involves collecting data on individuals' experiences at much more frequent intervals than traditional survey research. This aspect of ESM makes it well-suited to examine time-specific aspects of students' experiences, as well as changes due to the disruptive effects of COVID-19. more »« less
Van Osch, W.; Cherchiglia, L.; Averkiadi, E.; Liang, Y.
(, International Conference on Human-Computer Interaction)
null
(Ed.)
This paper explores the adoption of a group-based Enterprise Social Media (ESM) tool (i.e., Microsoft Teams) in the context of a mid-sized undergraduate course in Information and Technology Management (ITM), thereby providing insights into the use and design of tools for group-based learning settings. The study used a mixed-methods approach—interviews, surveys, and server-side (i.e., objective) data—to investigate the effects of three core ESM affordances (i.e., editability, persistence, and visibility) on students’ perceptions of ESM functionality and efficiency, and in turn, on ESM-enabled perceived team productivity as well as the students’ level of system usage. Through leveraging a combination of qualitative and quantitative (both unobtrusive and self-reported) data, this paper aims to provide insights into the use of ESMs in group-based classrooms which is a theme of great importance given the need for high-quality online education experiences, especially during the current pandemic.
Lishinski, Alex; Rosenberg, Joshua
(, Proceedings of the 17th ACM Conference on International Computing Education Research)
Ko, A. K.
(Ed.)
There are significant participation gaps in computing, and the way to address these participation gaps lies not simply in getting students from underrepresented groups into a CS1 classroom, but supporting students to pursue their interest in computing further beyond CS1. There are many factors that may influence students’ pursuit of computing beyond introductory courses, including their sense that they can do what CS courses require of them (their self-efficacy) and positive emotional experiences in CS courses. When interest has been addressed in computing education, research has treated it mostly as an outcome of particular pedagogical approaches or curricula; what has not been studied is how students’ longer-term interest develops through more granular experiences that students have as they begin to engage with computing. In this paper, we present the results of a study designed to investigate how students’ interest in computing develops as a product of their momentary self-efficacy and affective experiences. Using a methodology that is relatively uncommon to computer science education—the experience sampling method, which involves frequently asking students brief, unobtrusive questions about their experiences—we surveyed CS1 students every week over the course of a semester to capture the nuances of their experiences. 74 CS1 students responded 14-18 times over the course of a semester about their self-efficacy, frustration, and situational interest. With this data, we used a multivariate, multi-level statistical model that allowed us to estimate how students’ granular, momentary experiences (measured through the experience sampling method surveys) and initial interest, self-efficacy, and self-reported gender (measured through traditional surveys) relate to their longer-term interest and achievement in the course. We found that students’ momentary experiences have a significant impact on their interest in computing and course outcomes, even controlling for the self-efficacy and interest students reported at the beginning of the semester. We also found significant gender differences in students’ momentary experiences, however, these were reduced substantially when students’ self-efficacy was added to the model, suggesting that gender gaps could instead be self-efficacy gaps. These results suggest that students’ momentary experiences in CS1, how they experience the course week to week, have an impact on their longer-term interest and learning outcomes. Furthermore, we found that male and female students reported different experiences, suggesting that improving the CS1 experiences that students have could help to close gender-related participation gaps. In all, this study shows that the granular experiences students have in CS1 matter for key outcomes of interest to computing education researchers and educators and that the experience sampling method, more common in fields adjacent to computer science education, provides one way for researchers to integrate the experiences students have into our accounts of why students become interested in computing.
This study aims to examine the current experiences of high school students in computer science (CS) courses and the factors that motivated them to continue their future enrollment. The participants were 603 high school students in grades 9 through 12 in Indiana, all of whom enrolled in at least one CS course during the 2020-2021 academic year. This research revealed that fun and meaningful CS pedagogy, knowledgeable CS teachers, and relevance to their lives and future careers enabled high school students to hold positive experiences in their CS classes. These experiences impacted students to take additional CS courses. In addition to these positive experiences, gender and early exposure to CS emerge as predictors to pursue CS courses. The findings will carry significance for policymakers and educators offering insights to enhance and broaden students’ participation and engagement in the CS course.
Practitioners delivering computer science (CS) education during the COVID-19 pandemic have faced numerous challenges, including the move to online learning. Understanding the impact on students, particularly students from historically marginalized groups within the United States, requires deeper exploration. Our research question for this study was: \textit{In what ways has the high school computer science educational ecosystem for students been impacted by COVID-19, particularly when comparing schools that have student populations with a majority of historically underrepresented students to those that do not?} To answer this question, we used the CAPE theoretical framework to measure schools’ Capacity to offer CS, student Access to CS education, student Participation in CS, and Experiences of students taking CS \cite{fletcherwarner2021cape}. We developed a quantitative instrument based on the results of a qualitative inquiry, then used the instrument to collect data from CS high school practitioners located in the United States (n=185) and performed a comparative analysis of the results. We found that the numbers of students participating in AP CS A courses, CS related as well as non-CS related extracurricular activities, and multiple extracurricular activities increased. However, schools primarily serving historically underrepresented students had significantly fewer students taking additional CS courses and fewer students participating in CS related extracurricular activities. Student learning in CS courses decreased significantly; however, engagement did not suffer. Other noncognitive factors, like students’ understanding of the relevance of technology and confidence using technology, improved overall; however, student interested in taking additional CS courses was significantly lower in schools primarily serving historically underrepresented students. Last, the numbers of students taking the AP CS A and AP CS Principles exams declined overall.
Practitioners delivering computer science (CS) education during the COVID-19 pandemic have faced numerous challenges, including the move to online learning. Understanding the impact on students, particularly students from historically marginalized groups within the United States, requires deeper exploration. Our research question for this study was: In what ways has the high school computer science educational ecosystem for students been impacted by COVID-19, particularly when comparing schools that have student populations with a majority of historically underrepresented students to those that do not? To answer this question, we used the CAPE theoretical framework to measure schools’ Capacity to offer CS, student Access to CS education, student Participation in CS, and Experiences of students taking CS. We developed a quantitative instrument based on the results of a qualitative inquiry, then used the instrument to collect data from CS high school practitioners located in the United States (n=185) and performed a comparative analysis of the results. We found that the numbers of students participating in AP CS A courses, CS related as well as non-CS related extracurricular activities, and multiple extracurricular activities increased. However, schools primarily serving historically underrepresented students had significantly fewer students taking additional CS courses and fewer students participating in CS related extracurricular activities. Student learning in CS courses decreased significantly; however, engagement did not suffer. Other noncognitive factors, like students’ understanding of the relevance of technology and confidence using technology, improved overall; however, student interested in taking additional CS courses was significantly lower in schools primarily serving historically underrepresented students. Last, the numbers of students taking the AP CS A and AP CS Principles exams declined overall.
Lishinski, Alex, Rosenberg, Joshua, Mann, Michael, Sultana, Omiya, and Dunn, Joshua. How CS1 Students Experienced COVID-19 In the Moment: Using An Experience Sampling Approach to Understand the Transition to Emergency Remote Instruction. Retrieved from https://par.nsf.gov/biblio/10288355. SIGCSE '21: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education . Web. doi:10.1145/3408877.3439657.
Lishinski, Alex, Rosenberg, Joshua, Mann, Michael, Sultana, Omiya, & Dunn, Joshua. How CS1 Students Experienced COVID-19 In the Moment: Using An Experience Sampling Approach to Understand the Transition to Emergency Remote Instruction. SIGCSE '21: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education, (). Retrieved from https://par.nsf.gov/biblio/10288355. https://doi.org/10.1145/3408877.3439657
Lishinski, Alex, Rosenberg, Joshua, Mann, Michael, Sultana, Omiya, and Dunn, Joshua.
"How CS1 Students Experienced COVID-19 In the Moment: Using An Experience Sampling Approach to Understand the Transition to Emergency Remote Instruction". SIGCSE '21: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (). Country unknown/Code not available. https://doi.org/10.1145/3408877.3439657.https://par.nsf.gov/biblio/10288355.
@article{osti_10288355,
place = {Country unknown/Code not available},
title = {How CS1 Students Experienced COVID-19 In the Moment: Using An Experience Sampling Approach to Understand the Transition to Emergency Remote Instruction},
url = {https://par.nsf.gov/biblio/10288355},
DOI = {10.1145/3408877.3439657},
abstractNote = {While computer science (CS) education researchers have frequently examined what happens in courses, programs of study, or occupations in general, they have less frequently addressed finer-grained experiences that spark students' interest in CS. One excellent way to study these types of student experiences is the Experience Sampling Method (ESM). ESM involves collecting data on individuals' experiences at much more frequent intervals than traditional survey research. This aspect of ESM makes it well-suited to examine time-specific aspects of students' experiences, as well as changes due to the disruptive effects of COVID-19.},
journal = {SIGCSE '21: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education},
author = {Lishinski, Alex and Rosenberg, Joshua and Mann, Michael and Sultana, Omiya and Dunn, Joshua},
editor = {Sherriff, M.}
}
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