Exploring Bimodality in Introductory Computer Science Performance Distributions

Basnet, Ram B.; Payne, Lori K; Doleck, Tenzin; Lemay, David John; Bazelais, Paul

doi:10.29333/ejmste/93190

Cited by 3 publications

(2 citation statements)

References 20 publications

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“…Indeed, this area of research has been the focus of both researchers and practitioners for many decades (Teo et al, 2019). There are several technology acceptance models that have been proffered to understand the process of technology adoption (Doleck et al, 2017a;Dwivedi et al, 2017): TRA, TAM, TPB, MPCU, IDT, and the Unified Theory of Acceptance and Use of Technology (UTAUT) model. These models…”

Section: Theoretical Frameworkmentioning

confidence: 99%

User acceptance and adoption dynamics of ChatGPT in educational settings

Bazelais,

Lemay,

Doleck

2024

EURASIA J Math Sci Tech Ed

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Recent developments in natural language understanding have sparked a great amount of interest in the large language models such as ChatGPT that contain billions of parameters and are trained for thousands of hours on all the textual data of the internet. ChatGPT has received immense attention because it has widespread applications, which it is able to do out-of-the-box, with no prior training or fine-tuning. These models show emergent skill and can perform virtually any textual task and provide glimmers, or “sparks”, of artificial general intelligence, in the form of a general problem solver as envisioned by Newell and Simon in the early days of artificial intelligence research. Researchers are now exploring the opportunities of ChatGPT in education. Yet, the factors influencing and driving users’ acceptance of ChatGPT remains largely unexplored. This study investigates users’ (n=138) acceptance of ChatGPT. We test a structural model developed using Unified Theory of Acceptance and Use of Technology model. The study reveals that performance expectancy is related to behavioral intention, which in turn is related to ChatGPT use. Findings are discussed within the context of mass adoption and the challenges and opportunities for teaching and learning. The findings provide empirical grounding to support understanding of technology acceptance decisions through the lens of students’ use of ChatGPT and further document the influence of situational factors on technology acceptance more broadly. This research contributes to body of knowledge and facilitates future research on digital innovation acceptance and use.

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Section: Theoretical Frameworkmentioning

confidence: 99%

User acceptance and adoption dynamics of ChatGPT in educational settings

Bazelais,

Lemay,

Doleck

2024

EURASIA J Math Sci Tech Ed

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“…Improving the academic results of CS1 courses can reduce student attrition, increase graduation rates, and increase the supply of qualified workers in scientific and technological fields to meet the growing demand. A wealth of research in computer science education has sought to explain why some students perform better than others in CS1 courses (Basnet et al, 2018;Guzdial, 2019;McCartney et al, 2017;Patitsas et al, 2019). One hypothesis for academic failure in CS1 courses relates to the cumulative nature of the materials and posits the existence of "stumbling points" in the learning path of programming: that is, there is a small number of identifiable skills and concepts that can have a major impact on a student's progress (Ahadi & Lister, 2013).…”

Section: Academic Failure In Cs1mentioning

confidence: 99%

Modularization for mastery learning in CS1: a 4-year action research study

2023

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Computer programming is a skill of increasing importance in scientific and technological fields. However, in introductory computer science (CS1) courses in higher education, approximately one in every three students fails. A common reason is that students are overwhelmed by an accelerated and inflexible pace of learning that jeopardizes success. Accordingly, in the computer science education literature it has been suggested that the pedagogical philosophy of 'mastery learning,' which supports students progressing at their own pace, can improve academic outcomes of CS1 courses. Nevertheless, few extended mastery learning implementations in CS1 have been documented in the literature, and there is a lack of guidance and best practices to foster its adoption. In this paper, we present a four-year action research study in which a modular mastery-based CS1 course was designed, evaluated and improved in successive iterations with cohorts of engineering freshmen in a Latin American research university (N = 959). In the first year of the intervention, only 19.3% of students passed the course in their first semester attempting it. In successive iterations, the instructional design, teaching and learning activities, course content, and course management were iteratively improved such that by the fourth year of offering 77.1% of students passed the course in their first semester. Over this period, course attrition was reduced from 25.0% to 3.8% of the cohort, and students' mean time spent in the course decreased from 23.2 weeks (SD = 7.38) to 14.9 (SD = 3.64). Results indicate that modularization for mastery learning is a viable approach for improving academic results in a CS1 course. Practical considerations towards successful implementation of this approach are presented and discussed.

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