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Automated Prediction of Novice Programmer Performance Using programming Trajectories 21st

Automated Prediction of Novice Programmer Performance Using ...

引用

21st International Conference on Artificial Intelligence in Education (AIED)

作者： Rubio, Miguel A. Univ Granada Dept Comp Sci Granada Spain

ISBN: (纸本)9783030522407;9783030522391

Online programming courses have become widely available and host thousands of learners every year. In these courses, participants must solve programming exercises by submitting partial solutions and checking the outcome. The sequence of partial solutions submitted by a student constitutes the programming trajectory followed by the student. In our work, we define a supervised machine learning algorithm that takes as input these programming trajectories and predicts whether a student will successfully complete the next exercise. We have validated our model with two different datasets: the first one is a set of problems from the online learning platform Robomission with over one hundred thousand exercises submitted. The second one comprises one hundred thousand exercises submitted to the Hour of Code challenge. The results obtained indicate that our model can accurately predict the future performance of the students. This work provides not only a new method to represent students' programming trajectories but also an efficient approach to predict the students' future performance. Furthermore, the information provided by the model can be used to select the students that would benefit from an intervention.

关键词： Machine learning introductory programming Novice programmer Educational data mining Block-based programming

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Self-Regulation, Self-Efficacy, and Fear of Failure Interactions with How Novices Use LLMs to Solve programming Problems 29

Self-Regulation, Self-Efficacy, and Fear of Failure Interact...

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29th Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE)

作者： Margulieux, Lauren E. Prather, James Reeves, Brent N. Becker, Brett A. Uzun, Gozde Cetin Loksa, Dastyni Leinonen, Juho Denny, Paul Georgia State Univ Atlanta GA 30303 USA Abilene Christian Univ Abilene TX 79699 USA Univ Coll Dublin Dublin Ireland Towson Univ Towson MD USA Aalto Univ Espoo Finland Univ Auckland Auckland New Zealand

ISBN: (纸本)9798400706004

We explored how undergraduate introductory programming students naturalistically used generative AI to solve programming problems. We focused on the relationship between their use of AI to their self-regulation strategies, self-efficacy, and fear of failure in programming. In this repeated-measures, mixed-methods research, we examined students' patterns of using generative AI with qualitative student reflections and their self-regulation, self-efficacy, and fear of failure with quantitative instruments at multiple times throughout the semester. We also explored the relationships among these variables to learner characteristics, perceived usefulness of AI, and performance. Overall, our results suggest that student factors affect their baseline use of AI. In particular, students with higher self-efficacy, lower fear of failure, or higher prior grades tended to use AI less or later in the problem-solving process and rated it as less useful than others. Interestingly, we found no relationship between students' self-regulation strategies and their use of AI. Students who used AI less or later in problem-solving also had higher grades in the course, but this is most likely due to prior characteristics as our data do not suggest that this is a causal relationship.

关键词： artificial intelligence Copilot CS1 fear of failure generative AI introductory programming large language models LLMs metacognition self-efficacy self-regulation self-regulated learning

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Feedback-Generation for programming Exercises With GPT-4 29

Feedback-Generation for Programming Exercises With GPT-4

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29th Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE)

作者： Azaiz, Imen Kiesler, Natalie Strickroth, Sven Ludwig Maximilians Univ Munchen Munich Germany Nuremberg Tech Nurnberg Germany

ISBN: (纸本)9798400706004

Ever since Large Language Models (LLMs) and related applications have become broadly available, several studies investigated their potential for assisting educators and supporting students in higher education. LLMs such as Codex, GPT-3.5, and GPT 4 have shown promising results in the context of large programming courses, where students can benefit from feedback and hints if provided timely and at scale. This paper explores the quality of GPT-4 Turbo's generated output for prompts containing both the programming task specification and a student's submission as input. Two assignments from an introductory programming course were selected, and GPT-4 was asked to generate feedback for 55 randomly chosen, authentic student programming submissions. The output was qualitatively analyzed regarding correctness, personalization, fault localization, and other features identified in the material. Compared to prior work and analyses of GPT-3.5, GPT-4 Turbo shows notable improvements. For example, the output is more structured and consistent. GPT-4 Turbo can also accurately identify invalid casing in student programs' output. In some cases, the feedback also includes the output of the student program. At the same time, inconsistent feedback was noted such as stating that the submission is correct but an error needs to be fixed. The present work increases our understanding of LLMs' potential, limitations, and how to integrate them into e-assessment systems, pedagogical scenarios, and instructing students who are using applications based on GPT-4.

关键词： formative feedback personalized feedback assessment introductory programming Large Language Models LLMs GPT-4 Turbo benchmarking

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CodeTailor: LLM-Powered Personalized Parsons Puzzles for Engaging Support While Learning programming 11

CodeTailor: LLM-Powered Personalized Parsons Puzzles for Eng...

引用

11h ACM Conference on Learning@Scale (L@S)

作者： Hou, Xinying Wu, Zihan Wang, Xu Ericson, Barbara J. Univ Michigan Ann Arbor MI 48109 USA

ISBN: (纸本)9798400706332

Learning to program can be challenging, and providing high-quality and timely support at scale is hard. Generative AI and its products, like ChatGPT, can create a solution for most intro-level programming problems. However, students might use these tools to just generate code for them, resulting in reduced engagement and limited learning. In this paper, we present CodeTailor, a system that leverages a large language model (LLM) to provide personalized help to students while still encouraging cognitive engagement. CodeTailor provides a personalized Parsons puzzle to support struggling students. In a Parsons puzzle, students place mixed-up code blocks in the correct order to solve a problem. A technical evaluation with previous incorrect student code snippets demonstrated that CodeTailor could deliver high-quality (correct, personalized, and concise) Parsons puzzles based on their incorrect code. We conducted a within-subjects study with 18 novice programmers. Participants perceived CodeTailor as more engaging than just receiving an LLM-generated solution (the baseline condition). In addition, participants applied more supported elements from the scaffolded practice to the posttest when using CodeTailor than baseline. Overall, most participants preferred using CodeTailor versus just receiving the LLM-generated code for learning. Qualitative observations and interviews also provided evidence for the benefits of CodeTailor, including thinking more about solution construction, fostering continuity in learning, promoting reflection, and boosting confidence. We suggest future design ideas to facilitate active learning opportunities with generative AI techniques.

关键词： Parsons Problems Personalization Large Language Models introductory programming GPT Generative AI Active Learning

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From Visual Arts to programming: Exploring the Impact on Achievement in Constructionist College CS1 Classes 29

From Visual Arts to Programming: Exploring the Impact on Ach...

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29th Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE)

作者： Campbell, Oladele O. Sanusi, Ismaila Temitayo Atagana, Harrison I. Niger State Polytech Zungeru Nigeria Univ South Africa Pretoria South Africa Univ Eastern Finland Joensuu Finland

ISBN: (纸本)9798400706004

In today's digital era, a diverse and proficient cohort in the computing field is essential for nations to operate, advance, and stay competitive. However, challenges persist in introducing newcomers to computing, particularly in the first programming course (CS1). By exploring the factors affecting student performance in CS1, we can gain valuable insight into the variables influencing student learning and outcomes. This study explored the impact of visual art background on the programming achievements of first-year college CS1 students. Data were collected from two cohorts of CS1 students who participated in quasi-experimental studies conducted at two polytechnics in north-central Nigeria. These students were the treatment groups exposed to Scratch programming according to constructionist pedagogy. The findings indicate that students with visual arts backgrounds consistently outperformed their peers, regardless of gender. Furthermore, the study examined how age and academic achievement levels interact with visual arts proficiency to predict programming success, and found that visual arts proficiency plays a critical role in determining programming achievement, regardless of these demographic factors. Considering these findings, this study offers valuable insights for programming educators to develop inclusive and engaging introductory programming classes. Incorporating engaging visual art concepts and activities into CS0 or pre-college CS curricula could benefit all students, especially those new to computing. Visual art proficiency may also predict programming success, guiding educators to provide additional support.

关键词： Constructionism introductory programming Novice programmers Visual art Spatial ability Inclusion Scratch CS1 Predictor Africa

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Regulatory Strategies for Novice programming Students 1

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15th International Conference on Computer Supported Education (CSEDU)

作者： Ferreira, Deller James Campos, Dirson Santos Goncalves, Anderson Cavalcante Univ Fed Goias Inst Informat Alameda Palmeiras Go Brazil

ISBN: (数字)9783031536564

ISBN: (纸本)9783031536557;9783031536564

Self-regulated learning holds great significance within the realm of introductory computer programming. It refers to the active involvement of students in their academic journey, encompassing motivational, behavioral, metacognitive, and cognitive aspects. In addition, the social regulation of learning plays a crucial role in programming education, wherein students collaborate to regulate their cognition, behavior, motivation, and emotions, fostering temporary coordination with peers or teachers. Unfortunately, current teaching and learning methodologies in programming tend to overlook the development of self-regulation, co-regulation, and shared regulation skills. Therefore, in this research we investigate the extent to which students in introductory programming employ regulation strategies during their programming endeavors. Through an exploratory study involving 198 (one hundred ninety-eight) participants, it was discovered that a significant number of students fail to engage in regulatory strategies while learning introductory programming. Consequently, there is a pressing need to implement strategies that support students' regulation during the learning process. To address this issue, 8 (eight) instructional scripts have been developed for teachers, incorporating evidence-based principles of programming learning and focusing on fostering regulatory strategies.

关键词： Self-regulation Co-regulation Socially shared regulation introductory programming

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B#: The Development and Assessment of an Iconic programming Tool for Novice Programmers

B#: The Development and Assessment of an Iconic Programming ...

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7th International Conference on Information Technology Based Higher Education and Training

作者： Greyling, J. H. Cilliers, C. B. Calitz, A. P. Nelson Mandela Metropolitan Univ Dept Comp Sci & Informat Syst POB 77000 ZA-6031 Port Elizabeth South Africa

ISBN: (纸本)9781424404056

The higher incidence of under-prepared students in the South African education institutions has a particular significance for introductory programming courses which rely heavily on the use of technological tools as components of the teaching model. Difficulties experienced by novice programmers in introductory programming courses include deficiencies in problem-solving strategies, misconceptions relating to programming language constructs and the use of traditional programming environments. An introductory programming course should offer students problem solving analysis and design experience as well as exposure to the basic ideas of algorithmic thinking. Generally, introductory programming courses tend to concentrate on the syntax of a programming language at the expense of developing problem solving skills. Coupled to this are the ever-increasing complexity of modern programming languages and the user interfaces of their IDEs. A strategy that addresses the difficulties experienced by novice programmers in introductory programming courses is one that modifies the teaching model, specifically within the context of technological support. One way of implementing this strategy is with the use of visual programming languages, of which the iconic flowchart approach is one. Further, iconic programming environments traditionally attempt to simplify the programming task by reducing the level of precision and manual typing usually required in the conventional textual programming languages. These environments also attempt to increase the speed at which problem-solving and implementation efforts occur. Consequently, B# was developed in order to provide an environment in which programs can be developed using iconic flowcharts. Basic programming concepts such as assignments, conditions, loops, inputs and outputs are supported. Automatic code generation, debugging and program execution is also supported by the system. This paper reports on the development of B#, focussing on insi

关键词： flowcharts iconic programming introductory programming

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Fostering Student Involvement and Collaboration in a Non-Majors' programming Course

Fostering Student Involvement and Collaboration in a Non-Maj...

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40th Annual Frontiers in Education Conference

作者： Rosiene, Carolyn Pe Rosiene, Joel A. Univ Hartford Hartford CT 06117 USA Eastern Connecticut State Univ Willimantic CT 06226 USA

ISBN: (纸本)9781424462599

The ubiquitous lecture, using a slide show or the traditional blackboard, is, arguably, best used at the end of an introduction to a programming topic, not at the onset. This paper documents a technique which demonstrates that illustrating the programming construct and syntax is best delivered through an example, by showing students actual code samples, actual runs, demonstrations, and tests, before the syntax of the construct is introduced. Moreover, one student from the class is selected to act as the "typist" (rather than the instructor) to enter code into the IDE which is visible to the rest of the class. By introducing the student to a well-structured illustration and having students get first-hand experience on the subject matter, students are more involved in the classroom, participate and play a role towards attaining the lesson's goals. This is supported with empirical data that shows students' inclination toward the idea of partaking in an active, collaborative classroom.

关键词： Non-majors introductory programming non-majors computing collaborative programming

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LEARNING COMPUTER programming WITH GAME DESIGN

LEARNING COMPUTER PROGRAMMING WITH GAME DESIGN

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1st International Conference on Computer Supported Education

作者： Dalal, Parth Dalal, Nikunj Kak, Subhash Oklahoma State Univ Dept Comp Sci Stillwater OK 74078 USA Oklahoma State Univ Dept Management Informat Syst Stillwater OK 74078 USA

ISBN: (纸本)9789898111821

We describe a teaching approach that introduces the computer science and information systems student to programming ideas using game design. Game-creation software that requires little or no programming knowledge is used for this purpose. Students construct a simple game using the software, and later they convert their game events to pseudo-code written using standard programming constructs. This rapid game creation teaching module can be implemented rather quickly and can be used as a precursor to the teaching of a formal programming language. In this paper, we overview the pedagogical model, discuss a rapid game creation tool, present a teaching plan, and outline the potential benefits of this approach.

关键词： Rapid game creation Game design introductory programming Learning Game creation software

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Toward a Smart Tool for Supporting programming Lab Work 19th

Toward a Smart Tool for Supporting Programming Lab Work

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19th International Conference on Augmented Intelligence and Intelligent Tutoring Systems (ITS)

作者： Bey, Anis Champagnat, Ronan La Rochelle Univ La Rochelle France Higher Sch Management Sci Annaba Algeria

ISBN: (纸本)9783031328824;9783031328831

In a lab work session, students may spend an inordinate amount of time attempting to correct simple errors, repeatedly revisiting and repeating the same errors due to the limited access to the tutor. Instructors, on the other hand, frequently find themselves explaining the same errors. This tool is designed to improve the educational environment in the computer lab for both students and instructors. The first experiment did not show that the tool improves learning programming, but it showed some insights about students that use the tool only in face-to-face sessions and students that use it only with the training mode compared to a control group.

关键词： Smart lab introductory programming Intelligent Tutoring System Feedback Learning Analytics

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