Many learners find the study of introductory computer programming difficult. This is also true of children with attention deficit hyperactivity disorder (ADHD), and we need an improved understanding of how they learn programming. After reviewing the constructivist approach to teaching and learning and investigating ADHD, this study explored strategies for constructive learning of introductory programming. The aim was to evaluate the effectiveness of the Karplus learning cycle to teach introductory programming. This was done through qualitative research from an interpretive perspective. Action research techniques were employed and data analysed using grounded theory methods. Four major constructivist teaching categories emerged, all of which support the use of the Karplus cycle. It is concluded that the three-phase Karplus cycle can be used to assist these learners learn introductory programming. However, it needs to be understood more broadly and the middle phase broken into two subphases to ensure effective learning. / Mathematical Sciences / M. Sc. (Mathematical Sciences)

Many learners find the study of introductory computer programming difficult. This is also true of children with attention deficit hyperactivity disorder (ADHD), and we need an improved understanding of how they learn programming. After reviewing the constructivist approach to teaching and learning and investigating ADHD, this study explored strategies for constructive learning of introductory programming. The aim was to evaluate the effectiveness of the Karplus learning cycle to teach introductory programming. This was done through qualitative research from an interpretive perspective. Action research techniques were employed and data analysed using grounded theory methods. Four major constructivist teaching categories emerged, all of which support the use of the Karplus cycle. It is concluded that the three-phase Karplus cycle can be used to assist these learners learn introductory programming. However, it needs to be understood more broadly and the middle phase broken into two subphases to ensure effective learning. / Mathematical Sciences / M. Sc. (Mathematical Sciences)

Submitted by Marília Sousa (mariliamariafeitoza@gmail.com) on 2018-07-26T12:25:36Z No. of bitstreams: 3 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertação Marília.pdf: 1106096 bytes, checksum: 5f4d3a102f590e08a72c6af9ef02d2e4 (MD5) folha de aprovação.pdf: 114224 bytes, checksum: 83acb0aa4ff29dd5cc1364b9b391ac77 (MD5) / Approved for entry into archive by Secretaria PPGI (secretariappgi@icomp.ufam.edu.br) on 2018-07-26T18:20:47Z (GMT) No. of bitstreams: 3 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertação Marília.pdf: 1106096 bytes, checksum: 5f4d3a102f590e08a72c6af9ef02d2e4 (MD5) folha de aprovação.pdf: 114224 bytes, checksum: 83acb0aa4ff29dd5cc1364b9b391ac77 (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2018-07-27T12:39:14Z (GMT) No. of bitstreams: 3 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertação Marília.pdf: 1106096 bytes, checksum: 5f4d3a102f590e08a72c6af9ef02d2e4 (MD5) folha de aprovação.pdf: 114224 bytes, checksum: 83acb0aa4ff29dd5cc1364b9b391ac77 (MD5) / Made available in DSpace on 2018-07-27T12:39:15Z (GMT). No. of bitstreams: 3 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertação Marília.pdf: 1106096 bytes, checksum: 5f4d3a102f590e08a72c6af9ef02d2e4 (MD5) folha de aprovação.pdf: 114224 bytes, checksum: 83acb0aa4ff29dd5cc1364b9b391ac77 (MD5) Previous issue date: 2017-09-29 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The present work introduces the Educational Data Mining and an experiment involving prediction of partial exams. The experiment uses data of the Introduction to Computer Programming course of the Federal University of Amazonas and seeks to classify the students according to their grade, in a maximum of three classes: satisfactory, unsatisfactory and without concept (dropout students). As conclusion, there is a quantitative analysis with the predictive data. / O presente trabalho tem o intuito de apresentar a Mineração de Dados Educacionais e um experimento envolvendo previsão de provas parciais. O experimento é realizado através dos dados da disciplina de Introdução à Programação de Computadores da Universidade Federal do Amazonas e busca classificar os alunos de acordo com as notas obtidas, em no máximo três classes: satisfatório, insatisfatório e sem conceito (alunos evadidos). Como conclusão, tem-se uma análise quantitativa com os dados da previsão.

Purpose – The contradiction of the increased demand for IT specialists and the decrease of the enrollment in programming courses at universities worldwide has been discussed over the years. To tackle the problem, researchers and teachers in computing education have investigated various success factors in introductory programming courses, mostly within the context of computer science. This paper focuses on the investigation of success factors for students that are not majoring in computer science (non-CS) in an introductory programming course, to report on the results of student's performance and analysis of the most relevant success factors, also provide suggestions that could be considered for the course design and teaching method.   Method – The methods used to carry out the study are a survey with 36 participants, conducted before the start of an introductory programming course, and qualitative interviews conducted with twelve students after the end of the course. The interviews were then analysed thematically to find common patterns for five success factors between the students with different grades. The success factors that were examined are math background, previous programming experience, comfort level, motivation and attribution to success.   Findings – Math background could not be proved as a success factor in this study due to the lack of a standardized assessment of the students’ math levels. Previous programming experience could be regarded as a success factor but not as dominant as the success factor motivation, which has shown clear patterns in the data. Comfort level could be seen as one of the success factors as well, as most of the data in this study support this conclusion. Lastly, attribution to success as a success factor could not be supported by this study; the qualitative data showed variety which makes it hard to draw a conclusion directly.   Implications – The study suggest increasing the motivation for the non-CS students in introductory programming by combining programming with other subjects in the programme. The lecturer could customize the course for students with different interests so they could select a path and adapt the knowledge to their needs. Bridging courses and various forms of mentoring are also recommended to offer.   Limitations – The time frame of the study limited the amount of data that could be collected. The study was conducted with students from only one university and one non-CS programme, with a small data sample for analysis, which is limiting in the way the results can be generalized.

Providing a sufficient level of personalized feedback on students' current level of strategic knowledge within the context of the natural programming environment through IDE-based learning analytics would transform learning outcomes for introductory programming students. However, providing sufficient insight into the programming process was previously inaccessible due to the need for more complex and scalable data collection methods and metrics with a wider variety for understanding programming metacognition and the full programming process. This research developed a custom-built web-based IDE and event compression system to investigate two of the five components of a five-dimensional model of cognition for programming skill estimation (1) Design Cohesion and (2) Development Path over Time. The IDE captured students' programming process data for 25 participants, where each participated in two programming sessions that required both a design and code phase. For Design Cohesion, the alignment between flowchart design and source code implementation was investigated and manually classified. The classification process produced three Design Cohesion metrics: Design Cohesion Level, Granularity Level, and Granularity Score. The relationship between programming skill and Design Cohesion was explored using the newly developed metrics and a case-study approach. For the Development Path over Time, the compressed programming events were used to create a Timeline of Events for each participant, which was manually examined for distinct clusters of programming patterns and behavior such as execution behavior and debugging patterns. Custom visualizations were developed to display the timelines. Then, the timelines were used to compare programming behaviors for participants with different programming skill levels. The results of the investigation into Design Cohesion and Development Path Over Time contribute to the fundamental understanding of differences between beginner, intermediate, and advanced programmers and the context in which specific programming difficulties arise. This work produced insight into students' programming processes that can be used to advance the model of cognition for programming skill estimation and provide personalized feedback to support the development of programming skills and expertise. Additionally, this research produced tools and metrics that can be used in future studies examining programming metacognition.

Στην εργασία περιγράφεται η διαδικασία εξοικείωσης των μαθητών με το εκπαιδευτικό πακέτο της Αλγοριθμικής και τον προγραμματισμό μέσω μελέτης περίπτωσης ενός τμήματος ενιαίου Λυκείου. Η Αλγοριθμική είναι ένα ολοκληρωμένο πακέτο προγραμματιστικών περιβαλλόντων και εργαλείων για τη διδακτική υποστήριξη σεναρίων και δραστηριοτήτων ενταγμένων στα μαθήματα Πληροφορικής της Γ’ Γυμνασίου και των Α’, Β’ και Γ’ Λυκείου. Το περιβάλλον αυτό χρησιμοποιήθηκε για τη διδασκαλία της αλγοριθμικής σκέψης και του προγραμματισμού σε ένα τμήμα της Α’ τάξης ενιαίου Λυκείου. Στην εργασία παρουσιάζονται τα κυριότερα λάθη των μαθητών τόσο στο Δημιουργό Διαγραμμάτων Ροής όσο και στο Διερμηνευτή της Γλώσσας σε αρχικό στάδιο διδασκαλίας όσο και σε πιο προχωρημένο με τη χρήση της δομής επιλογής και συγκεκριμένα εμφωλευμένων ΑΝ. Κρίνεται η αποδοτικότητα των σεναρίων χρήσης της Αλγοριθμικής και γίνονται ορισμένες προτάσεις για τη βελτίωσή τους, καθώς και τη βελτίωση των εργαλείων ΔΔΡ και Διερμηνευτής της Γλώσσας για την καλύτερη χρήση από τους μαθητές. Τέλος, παρουσιάζονται κάποιες υλοποιήσεις μαθητών που είχαν καλή δομή κώδικα και ιδιαίτερη εφευρετικότητα. / The work describes the process of introducing students to computer programming and in particular with the educational package “Algorithmic”, through case study of a single Secondary School classroom. “Algorithmic” is a complete package of programming environments and tools to support teaching scenarios and integrated activities in Secondary School computer classrooms. This package was used in teaching algorithmic thinking and computer programming in a classroom of first grade Secondary School. The paper describes the main errors of students when creating flowcharts as well as computer programs using the software tool “GLOSSA”, in earlier teaching stages and later with the use of more advanced decision structures like nested IF statements. This work studies the efficiency of the usage scenarios of “Algorithmic” and makes suggestions for improving the software tools “flowchart” and “GLOSSA” to be more suitable to the level of students and to the course goals. Finally, the paper presents some well structured programming implementations of students.

This study was motivated by a desire to address the challenges of introductory programming courses. Ethiopian universities teach such courses in large classes (80+ students) and students complain about the difficulty of the courses and teaching variation of instructors. The study was set to explore optimum course and learning environment design approaches. The research question raised was: how can a blended learning approach be used to improve large class teaching of programming? In an action design research approach, the study was initiated with redesigning two consecutive courses and a supportive blended learning environment on the basis of existing learning theories and educational design frameworks. Two cycles of action research were conducted for a dual goal of refinement and evaluation of the intervention. The action research was conducted during the 2012/13 academic year with 240 students at the beginning. A predominantly quantitative first cycle of action research produced a mixed outcome. The students’ marks from assessment activities were fairly close to results from two other international universities. A pre- and post-implementation survey of students’ approach to learning showed a slight class level change towards the deep learning approach. Conversely, some students were found at-risk (not progressing well) and certain technologies, particularly program visualisation tools, were found underutilised. The second action research cycle aimed to explain the result from the first round. A grounded action research evaluation of data from focus group discussions, interviews and participants’ memos identified plausible factors for meaningful programming learning in a large class. These factors were use of collaborative and pair programming; alignment of learning and assignment activities; integrated use of e-learning; and use of large class strategies like student mentors and team teaching. A critical realist interpretation of the result of the action research suggested that students can learn programming in large classes, 200+ in this study, with a course and learning environment design that keeps them engaged in learning and assessment activities. The study concludes that improved learning of programming can be possible with the use of students as mentors and changed role-dynamics of instructors, which presupposes adaptation of suitable pedagogical approaches and use of technologies. / School of Computing / D. Litt. et Phil. (Information Systems)

Introductory programming failure rate among students is high worldwide, including in South Africa. The failure rate remains a subject for investigation due to a high number of students who find learning to program difficult. This study evaluates factors that contribute to high failure rates in an introductory programming module at University of South Africa. The study evaluates curriculum, programming syllabus, and personal factors to evaluate reasons for high failure rates. Quantitative and qualitative research approaches are used to identify learning hindrances. The research results show that personal factors are the leading contributing factors, followed by the curriculum and then the programming syllabus. Personal factors relate to time, personal reasons, and commitments; curriculum involves tutorials; and programming syllabus factors are linked to programming concepts and application. The findings have implications for how teaching and learning in introductory programming can be improved. The study provides recommendations for improvement and future studies. Keywords: Learn to program; introductory programming; higher learning; personal / School of Computing / M. Tech (Information Technology)

This study was motivated by a desire to address the challenges of introductory programming courses. Ethiopian universities teach such courses in large classes (80+ students) and students complain about the difficulty of the courses and teaching variation of instructors. The study was set to explore optimum course and learning environment design approaches. The research question raised was: how can a blended learning approach be used to improve large class teaching of programming? In an action design research approach, the study was initiated with redesigning two consecutive courses and a supportive blended learning environment on the basis of existing learning theories and educational design frameworks. Two cycles of action research were conducted for a dual goal of refinement and evaluation of the intervention. The action research was conducted during the 2012/13 academic year with 240 students at the beginning. A predominantly quantitative first cycle of action research produced a mixed outcome. The students’ marks from assessment activities were fairly close to results from two other international universities. A pre- and post-implementation survey of students’ approach to learning showed a slight class level change towards the deep learning approach. Conversely, some students were found at-risk (not progressing well) and certain technologies, particularly program visualisation tools, were found underutilised. The second action research cycle aimed to explain the result from the first round. A grounded action research evaluation of data from focus group discussions, interviews and participants’ memos identified plausible factors for meaningful programming learning in a large class. These factors were use of collaborative and pair programming; alignment of learning and assignment activities; integrated use of e-learning; and use of large class strategies like student mentors and team teaching. A critical realist interpretation of the result of the action research suggested that students can learn programming in large classes, 200+ in this study, with a course and learning environment design that keeps them engaged in learning and assessment activities. The study concludes that improved learning of programming can be possible with the use of students as mentors and changed role-dynamics of instructors, which presupposes adaptation of suitable pedagogical approaches and use of technologies. / School of Computing / D. Litt. et Phil. (Information Systems)

This thesis describes a research project aimed at improving the tracing skills of first-year programming students enrolled for an introductory C++ course at an open distance learning institution by means of a tutorial in the form of a program visualization tool to teach the students to draw variable diagrams. The research was based on the findings from the BRACElet project (Clear, Whalley, Robbins, Philpott, Eckerdal, Laakso & Lister, 2011). A design-based research methodology was followed. To guide the process of developing the tutorial, a framework of 26 guidelines for developing and using visualization tools to teach programming was synthesized from the literature on computing education research CER, educational psychology and computer graphics. Guidelines were supplemented with reasons or explanations for their recommendation and considerations to be taken into account when using a guideline. The framework was enhanced by lessons learnt during the development and testing of the tutorial. The tutorial was tested and refined during two implementation cycles. Both cycles included quantitative and qualitative investigations. All students registered for the introductory module received the tool with their study material. For the quantitative investigations, students completed a questionnaire after using the tutorial. Through the questionnaire biographical data was acquired, the manner in which students used the tutorial and how they experienced using it. The responses to the questionnaires were statistically analysed in combination with respondents’ final marks. The statistical modelling indicated that the students’ biographical properties (a combination of level of programming experience, marks obtained for Mathematics and English in matric and first-time registration for COS1511 or not), had the biggest impact on their final marks by far. During the qualitative investigations students were eye tracked in a Human-Computer Interaction laboratory. The gaze replays in both cycles revealed that students’ reading skills impacted largely on their success, connecting with the findings from the quantitative investigations. Reflections on why the tutorial did not achieve its purpose; and why poor reading skills may have such a strong effect on learning to program, contribute some theoretical understanding as to how novices learn to program. / Computer Science / D. Phil. (Computer Science)