Examining the intermediate programmers understanding of the learning process

Simkins, David; Decker, Adrienne

doi:10.1109/fie.2016.7757449

Cited by 4 publications

(4 citation statements)

References 3 publications

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“…Thomas et al (2012) remark on difficulties and problems students can experience in a Comp-Arch course due to abstract concepts. Simkins & Decker (2016) and Omer, Farooq & Abid (2021) show that students grasp limited knowledge and the course itself becomes inefficient when teaching methods focus only on theoretical concepts ( Simkins & Decker, 2016 ; Omer, Farooq & Abid, 2021 ; Yehezkel et al, 2001 ; Kehagias, 2016 ). Anderson & Nguyen (2005) survey the literature to find the best assignments for their course to avoid students struggling in the theoretical parts of an operating systems course.…”

Section: Related Workmentioning

confidence: 99%

“…On the other hand, Patel & Patt (2019) state that the main issue is due to forcing students to memorize things before they understand the topic detailed. Simkins & Decker (2016) survey the difficulties that students encounter during programming courses. About 41% of students who encounter difficulties in “Tools for Learning” state that the main reason is lack of practice.…”

Section: Related Workmentioning

confidence: 99%

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Teaching computer architecture by designing and simulating processors from their bits and bytes

Doğan,

Öztoprak,

Tolun

2024

PeerJ Computer Science

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Teaching computer architecture (Comp-Arch) courses in undergraduate curricula is becoming more of a challenge as most students prefer software-oriented courses. In some computer science/engineering departments, Comp-Arch courses are offered without the lab component due to resource constraints and differing pedagogical priorities. This article demonstrates how students working in teams are motivated to study the Comp-Arch course and how instructors can increase student motivation and knowledge by taking advantage of hands-on practices. The teams are asked to design and implement a 16-bit MIPS-like processor with constraints as a specific instruction set, and limited data and instruction memory. Student projects include following three phases, namely, design, desktop simulator implementation, and verification using hardware description language (HDL). In the design phase, teams develop their Comp-Arch to implement specified instructions. A range of designs resulted, e.g., (a) a processor with extensive user-defined instructions resulting in longer cycle times (b) a processor with a minimal instruction set but with a faster clock cycle time. Next, teams developed a desktop simulator in any programming language to execute instructions on the architecture. Finally, students engage in Verilog Hardware Description Language (HDL) projects to simulate and verify the data-path designed during the initial phase. Student feedback and their current understanding of the project were collected through a questionnaire featuring varying Likert scale questions, some with a ten-point scale, and others with a five-point scale. Results of the survey show that the hands-on approach increases students’ motivation and knowledge in the Comp-Arch course, which is centered around computer system design principles. This approach can also be effectively extended to related courses, such as Microprocessor Design, which delves into the intricacies of creating and implementing microprocessors or central processing units (CPUs) at the hardware level. Furthermore, the present study demonstrates that interactions, specifically through peer reviews and public presentations, between students in each phase increases their knowledge and perspective on designing custom processors.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Teaching computer architecture by designing and simulating processors from their bits and bytes

Doğan,

Öztoprak,

Tolun

2024

PeerJ Computer Science

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“…McCall & Kölling, 2019; Ullah et al, 2019;Ureel & Wallace, 2019;Albluwi, 2018;Bhatia, Kohli & Singh, 2018;Lagus et al, 2018;Lin et al, 2018;Turner, Pérez-Quiñones & Edwards, 2018;Wainer & Xavier, 2018;Castro-Wunsch, Ahadi & Petersen, 2017;Ahadi, Hellas & Lister, 2017;Echeverría et al, 2017;Hsiao, Huang & Murphy, 2017;Malliarakis, Satratzemi & Xinogalos, 2016;Scott et al, 2015;Xinogalos, 2015;Allinjawi, Al-Nuaim & Krause, 2014;Omer, Farooq & Abid, 2020 Greater or equal to 4 and less than 5 18Azcona, Hsiao & Smeaton, 2018;Esteero et al, 2018;Gomes & Correia, 2018;King, 2018;Koong et al, 2018;Premchaiswadi, Porouhan & Premchaiswadi, 2018;Dorodchi, Dehbozorgi & Frevert, 2017;España-Boquera et al, 2017;Estey, Keuning & Coady, 2017;Fu et al, 2017;Kumar, 2017;Seanosky et al, 2017;Seeling & Eickholt, 2017;Gomes, Correia & Abreu, 2016;Seeling, 2016;Simkins & Decker, 2016;Ahadi et al, 2015;Ashenafi, Riccardi & Ronchetti, 2015;Carter, Hundhausen & Adesope, 2015;Hilton & Rague, 2015;Janke, Br...…”

Section: Year-wise Publication Trendsmentioning

confidence: 99%

“…A study presented a model to analyze learning and predict students' performance (Liao et al, 2019). Similarly, another model was proposed to systematically identify errors in students' programs Azcona, Hsiao & Smeaton, 2018;Gomes & Correia, 2018;King, 2018;Santana, Figueredo & Bittencourt, 2018;Dorodchi, Dehbozorgi & Frevert, 2017;Kumar, 2017;Seeling & Eickholt, 2017;Gomes, Correia & Abreu, 2016;Zur & Vilner, 2014;Seeling, 2016;Simkins & Decker, 2016;Ashenafi, Riccardi & Ronchetti, 2015;Hilton & Rague, 2015;Rubio et al, 2014;Rosiene & Rosiene, 2015;Su et al, 2015 (Bhatia, Kohli & Singh, 2018). Experiments were performed to investigate various facets of IPC, which include difficulties of learning (Gomes & Correia, 2018;Xinogalos, 2015) and effectiveness of specific assessment techniques (King, 2018).…”

Section: Year-wise Publication Trendsmentioning

confidence: 99%

Introductory programming course: review and future implications

Omer

Farooq

Abid

2021

PeerJ Computer Science

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The introductory programming course (IPC) holds a special significance in computing disciplines as this course serves as a prerequisite for studying the higher level courses. Students generally face difficulties during their initial stages of learning how to program. Continuous efforts are being made to examine this course for identifying potential improvements. This article presents the review of the state-of-the-art research exploring various components of IPC by examining sixty-six articles published between 2014 and 2020 in well-reputed research venues. The results reveal that several useful methods have been proposed to support teaching and learning in IPC. Moreover, the research in IPC presented useful ways to conduct assessments, and also demonstrated different techniques to examine improvements in the IPC contents. In addition, a variety of tools are evaluated to support the related course processes. Apart from the aforementioned facets, this research explores other interesting dimensions of IPC, such as collaborative learning, cognitive assessments, and performance predictions. In addition to reviewing the recent advancements in IPC, this study proposes a new taxonomy of IPC research dimensions. Furthermore, based on the successful practices that are listed in the literature, some useful guidelines and advices for instructors have also been reported in this article. Lastly, this review presents some pertinent open research issues to highlight the future dimensions for IPC researchers.

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