Computing as the 4th “R”: a general education approach to computing education

Computing and computation are increasingly pervading our lives, careers, and societies - a change driving interest in computing education at the secondary level. But what should define a "general education" computing course at this level? That is, what would you want every person to know, assuming they never take another computing course? We identify possible outcomes for such a course through the experience of designing and implementing a general education university course utilizing best-practice pedagogies. Though we nominally taught programming, the design of the course led students to report gaining core, transferable skills and the confidence to employ them in their future. We discuss how various aspects of the course likely contributed to these gains. Finally, we encourage the community to embrace the challenge of teaching general education computing in contrast to and in conjunction with existing curricula designed primarily to interest students in the field

A LTIHub for Composite Assignments

Learning management systems (LMS) such as Canvas and Blackboard use Learning Tool Interoperability (LTI) as their main integration point for external learning tools. Each external tool provider has to implement LTI specifications or follow LTI standards that is a time consuming and complex process as there is no easy to follow specification available. Through this project, I have developed a system that follows the LTI specifications and integrates the CodeCheck autograder and interactive exercises with any LMS. I developed a Java based web app named LTIHub that acts as a mediator between LMS and any Learning Tool Provider. The LTIHub takes care of the LTI specification. The Learning Tool Provider needs to provide URL for each problem and a callback URL. This application stores the information related to the status of assignments and passes the information back to the LMS when all problems of an assignment are done by a student. I have prepared this report on the architecture of the software and analysis of students data during a semester of deployment

Analysis on C++ Topic Difficulties Ranking: A Case Study on Mechanical Engineering Students in UiTM Pasir Gudang

The aim of this paper is to analyse student’s performance obtained from the course “Fundamentals of Computer Problem Solving” (CSC128) final examination results. This is a C++ programming course and it is a mandatory subject for all Diploma in Mechanical Engineering and Diploma in Civil Engineering students at Universiti Teknologi MARA Pasir Gudang Campus. Through the analysis, this paper identify which topics in CSC128 is not being well mastered by the students.  The data was collected from 163 students score marks and the analysis was conducted by categorizing the final examination questions into five different topics according to CSC128 syllabus. An indicator has been used to classify students’ performance for each topic by comparing the percentage of students who scored 50% above and below of total marks for every topic. The study identified that Topic 4, “Repetition Control Structure” was placed in the first rank as the most difficult topic encountered by the students and Topic 3, “Selection Control Structure” was ranked as the least difficult topic. The findings will be used to improve the subject in order to achieve the course outcomes and can be a guideline for the lecturers to improve their teaching method in order to increase students’ understanding, interest and performance in programming

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

Proceedings of the Twentieth Conference of the Association of Christians in the Mathematical Sciences

The proceedings of the twentieth conference of the Associate of Christians in the Mathematical Sciences held at Redeemer University College from May 27-30, 2015

Factors influencing the learning of introductory computer programing at the Durban University of Technology.

Masters Degree. University of KwaZulu-Natal, Durban.Computer programming is an extremely difficult skill to master for students who are novice computer programmers. The preceding assertion is based on reports of high failure rates in introductory computer programming courses offered by tertiary education institutions. This is not just a South African problem but a number of cross-institutional and multi-national studies show that the problem is well known and is common (Grover et al., 2016). The current study investigated the factors influencing the learning of introductory computer programing at Durban University of Technology (DUT). The objectives of the study were to understand the influence of previous experience on students’ learning of introductory computer programming as well as to understand the influence of self-efficacy on students’ learning of introductory computer programming. The study also focused on understanding the influence of the ‘mental model ‘representation of the problem domain on students’ learning of introductory computer programming, and to understand the influence of the ‘mental model’ representation of the problem domain on students’ self-efficacy in the learning of introductory computer programming. The study adopted the quantitative research method to investigate the subject matter. This study embraced a survey research strategy and data collection carried out was over a short period. The study used simple random sampling to select 200 respondents at DUT. Data were collected using questionnaires. Data quality control was ensured by conducting a reliability and validity test on the data collection instrument used in this study. Ethical approval for the study was obtained from DUT. The quantitative data collected were analyzed using the SPSS, version 25.0. The study utilized statistics such as frequency, descriptive (mean and standard deviation) and inferential statistics (Cronbach’s alpha and Spearman correlation). The overall findings from the study suggested that the self-efficacy level of the research participants was high. The results of the study revealed that there was a moderate positive relationship between self-efficacy and computer programming. Furthermore, it found was that the mental model adopted by students when solving computer programming problems positively influences student performance in computer programming. An outcome of the study is the recommendation that the teaching and learning of computer programming should focus on language structure and the correct mental interpretation of the problem domain so that students could improve their performance

Pervasive learning analytics for fostering learners' self-regulation

Today's tertiary STEM (Science, Technology, Engineering and Mathematics) education in Europe poses problems to both teachers and students. With growing enrolment numbers, and numbers of teaching staff that are outmatched by this growth, student-teacher contact becomes more and more difficult to provide. Therefore, students are required to quickly adopt self-regulated and autonomous learning styles when entering European universities. Furthermore, teachers are required to divide their attention between large numbers of students. As a consequence, classical teaching formats of STEM education which often encompass experimentation or active exploration, become harder to implement. Educational software holds the promise of easing these problems, or, if not fully solving, at least of making them less acute: Learning Analytics generated by such software can foster self-regulation by providing students with both formative feedback and assessments. Educational software, in form of collaborative social media, makes it easier for teachers to collaborate, allows to reduce their workload and enables learning and teaching formats otherwise infeasible in large classes. The contribution of this thesis is threefold: Firstly, it reports on a social medium for tertiary STEM education called "Backstage2 / Projects" aimed specifically at these points: Improving learners' self-regulation by providing pervasive Learning Analytics, fostering teacher collaboration so as to reduce their workload, and providing means to deploy a variety of classical and novel learning and teaching formats in large classes. Secondly, it reports on several case studies conducted with that medium which point at the effectiveness of the medium and its provided Learning Analytics to increase learners' self-regulation, reduce teachers' workload, and improve how students learn. Thirdly, this thesis reports on findings from Learning Analytics which could be used in the future in designing further teaching and learning formats or case studies, yielding a rich perspective for future research and indications for improving tertiary STEM education

Evaluating Pedagogical Methods that Influence Homework Assignment Completion

College students enrolled in an online introductory engineering course are not completing their homework assignments at an acceptable rate which impacts them, the instructor, and the college. This research study employed a quasi-experimental evaluation model to assess the effectiveness of two pedagogical methods designed to positively influence student homework completion rates and student attitudes toward homework. Despite evidence that grading penalties encourage students to submit their homework assignments, such strategies have historically been unsuccessful for the course used in this study. The researcher designed two pedagogical interventions, along with a survey instrument, to measure the impact of the interventions on completion rates and student attitudes toward homework, using a combination of inferential and descriptive statistics. Ideally, the findings of this study would be generalizable to subsequent offerings of the course used in this study, as well as other courses taught by the investigator, and potentially other faculty at the college. Although both interventions did not produce statistically significant results on impacting student homework completion rates, or improve student attitudes toward homework, the results of the study did indicate a positive correlation between student self-assessed knowledge gains attributed to the course and its homework. One intervention did improve homework completion rates, but the results only marginally improved final course grades, which does not fully align with prior research studies. In addition, this study provided the researcher an opportunity to study their own practice and the importance of homework and its effectiveness for student learning

21st Century Physics Homework: A Mixed-Methods Approach Evaluating How an Individualized Online Homework Platform Can Provide Quality Feedback and Help Physics Students Engage in Self-Regulated Learning

American secondary students spend many hours each week working on homework. To get the most out of this homework, students need to receive quality feedback and engage in self-regulated learning when completing homework tasks. For teachers, traditional paper-and-pencil homework means extra time spent grading rather than giving good feedback. This study aims to answer the following questions: 1) How and to what extent does the implementation of individualized online homework and feedback impact self-regulated learning among Honors Physics high school students? and 2) How does the implementation of individualized online homework impact students’ perception of the feedback quality provided by an individualized online homework platform? To answer these questions, a convergent parallel mixed-methods study involving 14 secondary honors physics high school students in South Carolina was conducted. An individualized homework platform called Mastering Physics was introduced to the class in the fall of 2019. This platform individualizes student assignments with free-response questions that have randomized variables. Quantitative data about this intervention’s effectiveness in impacting the areas of student self-regulated learning skills and perception of feedback quality were collected with the following instruments: 1) Online Self-Regulated Learning Questionnaire (Barnard, Lan, To, Paton, & Lai, 2009) and 2) an adapted version of the Feedback Environment Survey (Steelman, Levy, & Snell, 2004). Qualitative data was collected in the form of two focus group interviews. Quantitative data were anlyzed using both descriptive and inferential statistics.Qualitative data, in the form of focus group transcriptions, were analyzed through memo writing, peer debriefing, first cycle coding and second cycle coding. The quantitative data did not reveal any significant differences which aligned with the qualitative data. Key findings are that participants’ SRL skills did not significantly improve and that students did not perceive the feedback they received as being high quality