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in-class coding Exercises As A Mechanism To Inform Early Intervention In Programming Courses 2025

In-class Coding Exercises As A Mechanism To Inform Early Int...

引用

56th Technical Symposium on Computer Science Education

作者： Hicks, Eric Phan, Vinhthuy Univ Memphis Memphis TN 38152 USA

ISBN: (纸本)9798400705328

Early intervention is critical in increasing student success in Computer Science (CS) courses, which have attracted a diverse student population. In-class exercises, which are often low-stake and quick assignments, are a popular method for active learning and formative assessment. This study explores the potential of using in-class coding exercises for early intervention in programming courses, particularly before midterm exams. We analyzed historical data from a CS1 course to evaluate whether in-class coding exercises can predict midterm exam performance. Our findings reveal that in-class coding exercises are effective predictors of midterm performance and can serve as valuable tools for early intervention. Specifically, exercise scores and time on task are sufficient indicators of student performance. Although in-class exercises are less powerful predictors than traditional metrics, they offer quicker actionable insights. Additionally, predicting students who are struggling is more feasible than forecasting those who will fail or achieve specific letter grades. This research underscores the potential for designing targeted intervention schemes to support students in CS1 and other programming courses, highlighting the importance of timely and data-driven support mechanisms.

关键词： active learning CS1 in-class coding performance modeling

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Enhancing Student Performance Prediction In CS1 Via in-class coding 2025

Enhancing Student Performance Prediction In CS1 Via In-Class...

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56th Technical Symposium on Computer Science Education

作者： Hicks, Eric Vinhthuy Phan Malasri, Kriangsiri Univ Memphis Memphis TN 38152 USA

ISBN: (纸本)9798400705311

Computer science's increased recognition as a prominent field of study has attracted students with diverse academic backgrounds. This has significantly increased the already high failure rates in introductory courses. To address this challenge, it is essential to identify struggling students early on. Incorporating in-class coding exercises in these courses not only offers additional practice opportunities to students but may also reveal their abilities and help teachers identify those in need of assistance. In this work, we seek to determine the extent to which the practice of using in-class coding exercises enhances the ability to predict student performance, especially early in the semester. Based on data obtained in a CS1 course taught at a mid-size American university, we found that in-class exercises could improve the prediction of students' eventual performance. In particular, we found relatively accurately predictions as early as academic weeks 3 through 5, making it possible to devise early intervention strategies. This work can benefit future studies on the impact of in-class exercises as well as intervention strategies throughout the semester.

关键词： active learning CS1 in-class coding performance modeling

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Keep It Relevant! Using In-class Exercises to Predict Weekly Performance in CS1 2022

Keep It Relevant! Using In-class Exercises to Predict Weekly...

引用

53rd Annual ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE)

作者： Hicks, Eric Cook, Amy Malasri, Kriangsiri Zaman, Alina Phan, Vinhthuy Univ Memphis Memphis TN 38152 USA

ISBN: (纸本)9781450390705

In large programming courses, it can be difficult for instructors to identify students who need help. Often the earliest indication of trouble is when a student fails an exam, which unfortunately can be too late. Using data from 7 sections of CS1 over multiple semesters, we show that performance on lab and in-class coding exercises can be used to accurately predict which students will fail or struggle on upcoming weekly lab assignments. We found that recent relevant in-class coding exercises were the best features for building accurate models. This approach has potential in helping CS1 instructors identify students who need help, determine which topics need additional attention, and formulate intervention plans, all on a weekly basis before each lab meeting.

关键词： active learning CS1 in-class coding

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Is More Active Always Better for Teaching Introductory Programming? 6

Is More Active Always Better for Teaching Introductory Progr...

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6th International Conference on Learning and Teaching in Computing and Engineering (LaTiCE)

作者： Raj, Adalbert Gerald Soosai Patel, Jignesh M. Halverson, Richard Univ Wisconsin Madison Comp Sci & Educ Madison WI 53706 USA Univ Wisconsin Madison Dept Comp Sci Madison WI USA Univ Wisconsin Madison Dept Educ Leadership & Policy Anal Madison WI USA

ISBN: (纸本)9781538678978

Introduction to programming is usually taught using a wide range of instructional techniques. Some common techniques among them are mini-lectures, live-coding and in-class coding. Each of these three techniques require varying level of student activity. In this study, we taught programming to a group of students using these three techniques. We collected data in the form of a survey to understand the students' perceptions on these three instructional techniques. The results suggest that students like techniques that require a moderate level of student activity (e.g., live-coding) more when compared to techniques that require a great deal of student activity (e.g., in-class coding). We believe that our work has the potential to help instructors design their instructional techniques using a student-centric approach.

关键词： Active-learning live-coding mini-lectures in-class coding

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