Enhancing problem‐solving skills of novice programmers in an introductory programming course. Issue 1 (6th September 2021)

• Record Type: Journal Article
• Authors: Malik, Sohail Iqbal; Mathew, Roy; Al‐Sideiri, Abir; Jabbar, Jasiya; Al‐Nuaimi, Rim; Tawafak, Ragad M.
• Is Part Of: Computer applications in engineering education. Volume 30:Issue 1(2022)
• Page Start: 174
• Page End: 194
• Publication Date: 2021-09-06
• Subjects: E‐learning -- novice programmer -- problem‐solving skills -- programming education -- pseudo‐code; Engineering -- Study and teaching (Higher) -- Periodicals; Engineering -- Computer-assisted instruction -- Periodicals; 620
• DOI: 10.1002/cae.22450
• Languages: English
• ISSNs: 1061-3773

Abstract

Abstract: Novices should focus both on problem‐solving skills and programming knowledge (syntax and semantics) in learning to program. Most introductory programming courses pay more attention to programming knowledge. This study introduces a PAAM model (Problem Analysis Algorithmic Model) in the teaching–learning process of the introductory programming (IP) course. The model focuses on problem statement requirements (input, output, and process) and problem‐solving skills for novices. A web application was developed to offer the model in the course. Two surveys were conducted to collect the responses of IP students. Semistructured interviews were performed with the IP instructors. The final exam grades of the IP course over the last two semesters were compared to determine the impact of the PAAM model on the students gain. Results show that most students appreciated the model in the teaching–learning process of the course. The model helps students to develop problem‐solving skills ( p = .002), understand problem statement inputs ( p = .003), process ( p = .004), outputs ( p = .034), and motivates them to learn programming ( p = .031). The application impacts positively on students' behavior and attitude toward completing the programming exercises in the course. Overall, the PAAM approach (11.1%) impacts positively by decreasing the attrition rate (9.9%) in the course when it is compared with the traditional approach (21.0%).