Motivation of Engineering Students with a Mixed-Contexts Approach to Introductory Programming

Santana, Bianca Leite; Figuerêdo, José Solenir Lima; Bittencourt, Roberto A.

doi:10.1109/fie.2018.8659158

Cited by 9 publications

(9 citation statements)

References 15 publications

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“…33 Chaweewan et al, 2018;Santana, Figueredo & Bittencourt, 2018;Ahmad et al, 2017;al-Rifaie, Yee-King & d'Inverno, 2017;Delev & Gjorgjevikj, 2017;Berges et al, 2016;Funabiki, Ishihara & Kao, 2016;Doshi, Christian & Trivedi, 2014;Chung & Hsiao, 2020;Effenberger, Pelánek & Čechák, 2020 Greater than 2 and less than 3…”

Section: Year-wise Publication Trendsmentioning

confidence: 99%

“…The time spent on performing various course related activities has been observed as a commonly utilized parameter to analyze learning in framework-based research (Chaweewan et al, 2018;Premchaiswadi, Porouhan & Premchaiswadi, 2018). The case studies were conducted, e.g., to check the effect of altering the content sequence (Janke, Brune & Wagner, 2015) and to identify the impact of teaching different programming languages on learning (Santana, Figueredo & Bittencourt, 2018). Improvement related work presented refinements on already conducted research.…”

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%

“…Motivation to learn programming was increased. Santana, Figueredo & Bittencourt, 2018 assigning weights to the instances that were involved in predictions. The learning approaches were examined, e.g., through different learning patterns (Echeverría et al, 2017), and by applying the genetic algorithms for identification of personalized learning needs (Lin et al, 2018).…”

Section: Xinogalos 2015mentioning

confidence: 99%

“…The research in IPC examined various ways of teaching, learning, and assessments to enhance the relevant aspects (Seeling & Eickholt, 2017;Funabiki, Ishihara & Kao, 2016;Rubio et al, 2014). In addition, the improvisations in contents of IPC have also been investigated in literature (Santana, Figueredo & Bittencourt, 2018;Wainer & Xavier, 2018). Moreover, efforts have also been made to evaluate the use of different tools in order to engage students and support the successful execution of IPC (Pereira et al, 2020;Ureel & Wallace, 2019).…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

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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Section: Year-wise Publication Trendsmentioning

confidence: 99%

Section: Year-wise Publication Trendsmentioning

confidence: 99%

Section: Year-wise Publication Trendsmentioning

confidence: 99%

Section: Xinogalos 2015mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Introductory programming course: review and future implications

Omer

Farooq

Abid

2021

PeerJ Computer Science

View full text Add to dashboard Cite

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Investigating the impact of adopting Python and C languages for introductory engineering programming courses

Balreira

Silveira

Wickboldt

2022

Comp Applic In Engineering

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Programming is one of the most fundamental initial skills for engineering students. Institutions that offer engineering courses have the challenge of deciding how to deliver this subject since it requires unique thinking from students. This paper addresses the impact of adopting C and Python programming languages in introductory programming courses for engineering students. A case study was conducted in the university's introductory programming course, analyzing student data. This approach divides the students into two groups according to the programming language: C and Python. Data were gathered and analyzed about their learning experiences through questionnaires, assignment scores, and students' questions posted in the class online forums. The experiment was repeated in two consecutive semesters. The main results favor Python regarding learning confidence, motivation, and general programming design decisions while favoring C for the easiness of learning data structures. This study may be helpful for institutions considering designing a new introductory programming course or redesigning existing ones.

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