An Examination of the Correlation of Exploring Computer Science Course Performance and the Development of Programming Expertise

McGee, Steven; Greenberg, Ronald I.; McGee-Tekula, Randi; Duck, Jennifer; Rasmussen, Andrew M.; Dettori, Lucia; Reed, Donald T.

doi:10.1145/3287324.3287415

Cited by 10 publications

(4 citation statements)

References 17 publications

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“…This is a highly impactful contribution to the CS field, specifically in the face of advocates against such 'non-programming specific CS courses' [15,35] and recent predictions on the importance of coding to influence postsecondary CS course success [3]. However, given recent research analyzing ECS's impact toward increasing the development of programming expertise among students who took the course [33], a connection between ECS and AP CS A is not far-fetched. Indeed, the predictive models for AP CS A exam passing did exhibit the importance of more systemic changes needed broadly across curriculum such as Intermediate Math Course success and the persistence of gender gaps in CS seen for decades [9,17,19,27,43], but also shed light on the equivalent passing rates across Black + Hispanic and Asian + white racial categorizations.…”

Section: Discussionmentioning

confidence: 99%

Broadening Participation and Success in AP CSA: Predictive Modeling from Three Years of Data

Boda

McGee

2021

Proceedings of the 52nd ACM Technical Symposium on Computer Science Education

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The AP Computer Science A course and exam continually exhibit inequity among over-and under-represented populations. This paper explored three years of AP CS A data in the Chicago Public School district (CPS) from 2016-2019 (N = 561). We analyzed the impact of teacher and student-level variables to determine the extent AP CS A course taking and exam passing differences existed between over-and under-represented populations. Our analyses suggest four prominent findings: (1) CPS, in collaboration with their Research-Practice Partnership (Chicago Alliance for Equity in Computer Science; CAFÉCS), is broadening participation for students taking the AP CS A course; (2) Overand under-represented students took the AP CS A exam at statistically comparable rates, suggesting differential encouragement to take or not take the AP CS A exam was not prevalent among these demographics; (3) After adjusting for teacher and student-level prior experience, there were no significant differences among over-and under-represented racial categorizations in their likelihoods to pass the AP CS A exam, albeit Female students were 3.3 times less likely to pass the exam than Males overall; (4) Taking the Exploring Computer Science course before AP CS A predicted students being 3.5 times more likely to pass the AP CS A exam than students that did not take ECS before AP CS A. Implications are discussed around secondary computer science course sequencing and lines of inquiry to encourage even greater broadening of participation in the AP CS A course and passing of the AP CS A exam.

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Section: Discussionmentioning

confidence: 99%

Broadening Participation and Success in AP CSA: Predictive Modeling from Three Years of Data

Boda

McGee

2021

Proceedings of the 52nd ACM Technical Symposium on Computer Science Education

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“…A similar practice is pursued in the evaluation of computer programming assessments, where rubrics are used to evaluate subjective programming tests, and students are required to produce codes and write down concepts to receive grades. For instance, McGee et al (2019) developed the scoring rubrics for the computer programming subjective assessment tasks. Chen et al ( 2020) also developed a 7-point scoring rubric for assessing student explanations of programming codes in plain English, a subjective assessment.…”

Section: Literature Reviewmentioning

confidence: 99%

Objective Assessment in Java Programming Language Using Rubrics

Priyanka¹,

Mehrotra²

2022

JITE:IIP

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Aim/Purpose: This paper focuses on designing and implementing the rubric for objective JAVA programming assessments. An unsupervised learning approach was used to group learners based on their performance in the results obtained from the rubric, reflecting their learning ability. Background: Students' learning outcomes have been evaluated subjectively using a rubric for years. Subjective assessments are simple to construct yet inconsistent and biased to evaluate. Objective assessments are stable, reliable, and easy to conduct. However, they usually lack rubrics. Methodology: In this study, a Top-Down assessment approach is followed, i.e., a rubric focused on the learning outcome of the subject is designed, and the proficiency of learners is judged by their performance in conducting the task given. A JAVA rubric is proposed based on the learning outcomes like syntactical, logical, conceptual, and advanced JAVA skills. A JAVA objective quiz (with multiple correct options) is prepared based on the rubric criteria, comprising five questions per criterion. The examination was conducted for 209 students (100 from the MCA course and 109 from B.Tech. course). The suggested rubric was used to compute the results. K-means clustering was applied to the results to classify the students according to their learning preferences and abilities. Contribution: This work contributes to the field of rubric designing by creating an objective programming assessment and analyzing the learners’ performance using machine learning techniques. It also facilitates a reliable feedback approach offering various possibilities in student learning analytics. Findings: The designed rubric, partial scoring, and cluster analysis of the results help us to provide individual feedback and also, group the students based on their learning skills. Like on average, learners are good at remembering the syntax and concepts, mediocre in logical and critical thinking, and need more practice in code optimization and designing applications. Recommendations for Practitioners: The practical implications of this work include rubric designing for objective assessments and building an informative feedback process. Faculty can use this approach as an alternative assessment measure. They are the strong pillars of e-assessments and virtual learning platforms. Recommendation for Researchers: This research presents a novel approach to rubric-based objective assessments. Thus, it provides a fresh perspective to the researchers promising enough opportunities in the current era of digital education. Impact on Society: In order to accomplish the shared objective of reflective learning, the grading rubric and its accompanying analysis can be utilized by both instructors and students. As an instructional assessment tool, the rubric helps instructors to align their pedagogies with the students’ learning levels and assists students in updating their learning paths based on the informative topic-wise scores generated with the help of the rubric. Future Research: The designed rubric in this study can be extended to other programming languages and subjects. Further, an adaptable weighted rubric can be created to execute a flexible and reflective learning process. In addition, outcome-based learning can be achieved by measuring and analyzing student improvements after rubric evaluation.

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“…This approval is only granted to select partners that play a central role in CPS. CAFÉCS has already published several reports based on these data [10]- [15].…”

Section: Building Trust and Cultivating Partnership Relationshipsmentioning

confidence: 99%

“…CAFÉCS has written research publications and presents at both research and practitioner conferences. For example, recent publications focus on ECS effects on student attitudes and computational thinking skills [10], [12], [13] and build on earlier research [5], [14], [15]. Members of CAFÉCS have also shared their experiences at CS4All RPP workshops (e.g., [16], [17]) and have provided periodic updates to congressional representatives from local districts.…”

Section: Supporting the Partner Practice Organization In Achieving Itmentioning

confidence: 99%

Assessing the Effectiveness of Computer Science RPPs: The Case of CAFÉCS

Henrick¹,

McGee

Greenberg

et al. 2019

2019 Research on Equity and Sustained Participation in Engineering, Computing, and Technology (RESPECT)

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Research Practice Partnerships (RPPs) are a relatively recent development as a potential strategy to address the complex challenges in computer science education. Consequently, there is little guidance available for assessing the effectiveness of RPPs. This paper describes the formative evaluation approach used to assess the progress of the first year of the formalized RPP, Chicago Alliance for Equity in Computer Science (CAFÉCS). This paper contributes to the RPP literature by providing a case study of how an RPP effectiveness framework can be adapted and used to inform partnership improvement efforts in computer science education.

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An Examination of the Correlation of Exploring Computer Science Course Performance and the Development of Programming Expertise

Cited by 10 publications

References 17 publications

Broadening Participation and Success in AP CSA: Predictive Modeling from Three Years of Data

Broadening Participation and Success in AP CSA: Predictive Modeling from Three Years of Data

Objective Assessment in Java Programming Language Using Rubrics

Assessing the Effectiveness of Computer Science RPPs: The Case of CAFÉCS

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