SimProgramming : the development of an integrated teaching approach for computer programming in higher education

Conferência realizada em Valência de 7-9 de março de 2016Computer programming courses in higher education tend to have high rates of academic failure and students struggle, particularly so in the transition from entry-level programming to advanced programming. Some of the reasons given in the literature relate to the type of teaching approach and the strategies used by students and their attitudes towards computer programming. The literature also mentions that educational approaches are not always appropriate to the needs of students and to the development of skills required in the job market. We developed a teaching approach to try to address some of these issues and support students learning computer programming in the transition from entry-level to advanced computer programming: the SimProgramming approach. This approach was introduced at the University of Trás-os-Montes e Alto Douro (Portugal), within the scope of the course “Programming Methodologies III”, part of the second curricular year of the programmes of studies in Informatics Engineering and in Information & Communication Technologies. We present in detail the origins of the SimProgramming approach, starting from the first trials that introduced, in two iterations, learning activities based on problem-based learning, and up to the third iteration where the current SimProgramming approach was implemented. We describe the reasoning, design and implementation of these three iterations, to show how the approach evolved. The SimProgramming approach is based in four conceptual foundations: business-like learning environment, self-regulated learning, co-regulated learning and formative assessment. For each of these conceptual foundations, we explain the teaching strategies adopted. In SimProgramming, the learning activity process develops in four phases, and students have specific tasks in each phase. We analyse interview data regarding student perceptions about the SimProgramming approach, and registration grids data on team work dynamics and final assessment of the assignment, noting the impact of SimProgramming in student grades. The application of SimProgramming revealed promising evidences in the overall results of student learning in the activities proposed in this approach. The average grades improved, and did the number of students regularly submitting their tasks on schedule. The perceptions of students regarding the SimProgramming approach are very positive: they recommend using it in the following years, and provided some suggestions to improve the approach. We conclude with reflections and recommendations for subsequent development of the SimProgramming approach in its application to the teaching of computer programming and potential for using it in other educational contexts.FC

Self-regulated learning in higher education : strategies adopted by computer programming students

Trabalho apresentado em PAEE/ALE’2016, 8th International Symposium on Project Approaches in Engineering Education (PAEE) and 14th Active Learning in Engineering Education Workshop (ALE)To help students overcome their learning difficulties in the transition from entry-level to advanced computer programming, developing an appropriate set of learning strategies, the SimProgramming teaching approach has been adopted at the University of Trás-os-Montes e Alto Douro (Portugal). This approach is based on four conceptual foundations: businesslike learning environment, self-regulated learning, co-regulated learning, and formative assessment. In this approach the students develop an activity based on problem-based learning, with a specific set of tasks based on those four conceptual foundations. The approach was implemented in two courses from the second and third curricular years of the bachelor programmes in Informatics Engineering and Information & Communication Technologies. We conducted semi-structured interviews with students (n=32) at the end of the courses, to try to identify the students’ strategies for self-regulation of learning in the activity developed within the SimProgramming approach. The main strategies identified were: organization, planning, time management, identification of difficulties, resolution of the difficulties encountered, work review, identification of the factors that influenced their motivation, and structure of the environment. The factors influencing the motivation most often identified by students were the impact of the assessment in the final course grade, the completion of the course, learning, skills development, and teamwork. Generally, students applied strategies to solve the difficulties, in particular by searching for social help and information search. Procrastination was also often identified by students. Strategies of time management, transformation of information, in-depth review, self-reflection, and self-evaluation were referenced scantily. We found that students changed some of their strategies from one course edition to the next. We conclude by recommending the development of educational practices to help students review their work, treat and process the information they find, conduct self-reflection and self-evaluation of their performance during tasks, adopt concentration strategies, and become aware of their specific difficulties

Source code analysis on student assignments using machine learning techniques

Abstract. To increase the success in computer programming courses, it is important to understand the learning process and common difficulties faced by students. Although several studies have investigated possible relationships between students performance and self-regulated learning characteristics, little attention has been given the source code produced by students in this regard. Such source code might contain valuable information about their learning process, specially in a context where practical programming assignments are frequent and students write source code constantly during the course. This poses the following research questions: What is the relationship between the characteristics of students source code and their performance in a computer programming course?. What is the relationship between source code features and self-regulated learning characteristics (i.e., motivation and learning strategies) in a computer programming course?. How the source code and self-regulated features can predict the students' performance? In order to answer these questions, a strategy to support the correlation analysis among students performance, motivation, use of learning strategies, and source code metrics in computer programming courses is proposed. A comprehensive case study is presented to evaluate the strategy. Additionally, an automatic grading tool for programming assignments was used, which facilitated to obtain the source code of the participants for further automatic source code analysis. Moreover, self-regulated learning characteristics were collected using the Motivated Strategies for Learning Questionnaire (MSLQ). Results show that the main features from source code which are significantly related to students performance and self-regulated learning features are: length-related metrics, with mainly positive correlations; and Halstead complexity measures, correlated negatively. In the light of the findings of this study, it is possible to understand better students source code as an artifact that can be used to monitorize several characteristics related to self-regulated learning, course performance, and in general, their learning process. In this way, more research in the area is required to verify if these relationships could give to computing educators new ways to identify and help students with problems.Para mejorar el éxito de los estudiantes en los cursos de programación, es importante entender el proceso de aprendizaje y las dificultades comunes que enfrentan los estudiantes. Aunque muchos estudios han investigado las posibles relaciones entre el rendimiento de los estudiantes y aspectos de la auto-regulación del aprendizaje, poca atención se le ha dado al código fuente producido por los estudiantes. El cual puede contener información valiosa acerca de su proceso de aprendizaje. Esto es especialmente cierto en contextos donde las actividades prácticas de programación son frecuentes y los estudiantes escriben código fuente constantemente durante el desarrollo del curso. Lo anterior, plantea las siguientes preguntas de investigación: ¿Cuál es la relación entre las características del código fuente de los estudiantes y su rendimiento en un curso de programación de computadores?. ¿Cuál es la relación entre las características del código fuente y características de aprendizaje auto-regulado (motivación y estrategias de aprendizaje) en un curso de programación de computadores?. ¿Cómo el código fuente y las características de aprendizaje auto-regulado pueden predecir el rendimiento de los estudiantes? Para responder estas preguntas, se presenta una estrategia para realizar el análisis de correlaciones entre el rendimiento de los estudiantes, motivación, el uso de estrategias de aprendizaje, y las métricas de código fuente en cursos de programación de computadores. Un caso de estudio exhaustivo es presentado para evaluar la estrategia propuesta usando datos recolectados de estudiantes. Además se usaba una herramienta de calificación automática para evaluar las practicas, lo cual facilitaba la obtención de código fuente de estudiantes para su análisis posterior. Las características de aprendizaje auto-regulado fueron obtenidas usando el cuestionario: Motivated Strategies for Learning Questionnaire Colombia (MSLQColombia). Los resultados muestran que las principales características del código fuente que están relacionadas con el rendimiento de los estudiantes y características auto-reguladas son: las métricas de longitud, que se correlaciona positivamente; y las medidas de complejidad de Halstead, las cuales se correlacionan negativamente. Dados los resultados, es posible entender mejor el código fuente de los estudiantes como un artefacto que puede ser usado para monitorear características relacionadas con el aprendizaje auto-regulado, rendimiento en el curso, y en general, su proceso de aprendizaje. De esta forma, investigaciones adicionales son necesarias para verificar si dichas relaciones pueden dar a los educadores nuevas herramientas para identificar y ayudar a estudiantes con problemas.Maestrí

The Effectiveness of Using Lego Mindstorms Robotics Activities to Influence Self-regulated Learning in a University Introductory Computer Programming Course.

The research described in this dissertation examines the possible link between self-regulated learning and LEGO Mindstorms robotics activities in teaching concepts in an introductory university computer programming course. The areas of student motivation, learning strategies, and mastery of course objectives are investigated. In all three cases analysis failed to reveal any statistically significant differences between the traditional control group and the experimental LEGO Mindstorms group as measured by the Motivated Strategies for Learning Questionnaire and course exams. Possible reasons for the lack of positive results include technical problems and limitations of the LEGO Mindstorms systems, limited number and availability of robots outside of class, limited amount of time during the semester for the robotics activities, and a possible difference in effectiveness based on gender. Responses to student follow-up questions, however, suggest that at least some of the students really enjoyed the LEGO activities. As with any teaching tool or activity, there are numerous ways in which LEGO Mindstorms can be incorporated into learning. This study explores whether or not LEGO Mindstorms are an effective tool for teaching introductory computer programming at the university level and how these systems can best be utilized

Introductory programming: a systematic literature review

As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research

Enhancing Practice and Achievement in Introductory Programming With a Robot Olympics

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