Introductory Programming Students Research Articles

Profiling the skill mastery of introductory programming students: A cognitive diagnostic modeling approach

Profiling the skill mastery of introductory programming students: A cognitive diagnostic modeling approach

Factors Influencing the Social Help-seeking Behavior of Introductory Programming Students in a Competitive University Environment

Collaboration is an important aspect of computing. In a classroom setting, working with others can increase a student’s motivation to attempt more challenges, reduce the difficulty of complicated concepts, and bring about greater overall success. Despite extensive research in other domains, there has been minimal exploration within computing on what impacts a student’s decision to seek social assistance in highly competitive university environments. To understand what affects introductory programming students’ social help-seeking behavior in this context, we conducted 32 semi-structured interviews with students and performed thematic analysis and qualitative coding on the ensuing transcripts. Our qualitative analysis revealed 18 significant factors. We noticed that the decision to seek social help involved a two-fold process: first, the decision to engage in social help-seeking, and subsequently, the decision of who to ask for help. Furthermore, we found that help-seeking in computing is not fundamentally different from other disciplines, although some of the factors were unique to the topic of computing and the specific environment of this study. Factors related to communication style, the type of question being asked, and the school’s cheating policy were central when discussing code, an integral part of computing. Regarding the environment, students repeatedly reported that the competitive major, the explicit and implicit class standards, and feelings of intimidation, among others, influenced them. These findings suggest that understanding both steps and the sociocultural context is important in order to effectively lower the barriers to asking for help.

SMAC-based Programming Learning Tool: Validating a Novel System Architecture

Although SMAC (Social, Mobile, Analytics, Cloud) allows pedagogical innovation due to its ability in expanding communication during the learning process, its exploitation for programming learning has yet to occur. Therefore, this study proposes a novel system architecture for a SMAC-based programming learning tool designed to enhance programming students’ problem-solving and collaborative skills. In evaluating the effectiveness of this architecture, this study conducted multiple two-week controlled experiments involving 71 introductory programming students. The experiment involves administering pre-and post-study surveys and tests to measure the enhancement in the two skills. The overall findings of this study indicated a statistically significant improvement in both the student’s problem-solving ability and collaborative skills. Most importantly, these findings suggest that the synergy of all four SMAC elements in a single programming learning tool has substantial benefits to programming learning.

Reevaluating the relationship between explaining, tracing, and writing skills in CS1 in a replication study

ABSTRACT Background and Context Lopez and Lister first presented evidence for a skill hierarchy of code reading, tracing, and writing for introductory programming students. Further support for this hierarchy could help computer science educators sequence course content to best build student programming skill. Objective This study aims to replicate a slightly simplified hierarchy of skills in CS1 using a larger body of students (600+ vs. 38) in a non-major introductory Python course with computer-based exams. We also explore the validity of other possible hierarchies. Method We collected student score data on 4 kinds of exam questions. Structural equation modeling was used to derive the hierarchy for each exam. Findings We find multiple best-fitting structural models. The original hierarchy does not appear among the “best” candidates, but similar models do. We also determined that our methods provide us with correlations between skills and do not answer a more fundamental question: what is the ideal teaching order for these skills? Implications This modeling work is valuable for understanding the possible correlations between fundamental code-related skills. However, analyzing student performance on these skills at a moment in time is not sufficient to determine teaching order. We present possible study designs for exploring this more actionable research question.

Machine Learning Prediction and Recommendation Framework to Support Introductory Programming Course

The new students struggle to understand the introductory programming courses, due to its intricate nature, which results in higher dropout and increased failure rates. Despite implementing productive methodologies, the instructor struggles to identify the students with distinctive levels of skills. The modern institutes are looking for technology-equipped practices to classify the students and prepare personalized consultation procedures for each class. This paper applies decision tree-based machine learning classifiers to develop a prediction model competent to forecast the outcome of the introductory programming students at an early stage of the semester. The model is then transformed into an adaptive consultation framework which generates three types of colored signals; red, yellow, and green which illustrates whether the student is performing low, average, or high respectively. This provides an opportunity for the instructor to set precautionary measures for low performing students and set complicated tasks that help the highly skilled students to improve their skills further. The experiments compare a set of decision tree-based classifiers and conclude J48 as an efficient model in classifying students in all classes with high accuracy, sensitivity, and F-measure. Even though the aim of the research is to focus on introductory programming courses, however, the framework is flexible and can be implemented in other courses.

Deep learning for early performance prediction of introductory programming students: a comparative and explanatory study

Introductory programming may be complex for many students. Moreover, there is a high failure and dropout rate in these courses. A potential way to tackle this problem is to predict student performance at an early stage, as it facilitates human-AI collaboration towards prescriptive analytics, where the instructors/monitors will be told how to intervene and support students - where early intervention is crucial. However, the literature states that there is no reliable predictor yet for programming students’ performance, since even large-scale analysis of multiple features have resulted in only limited predictive power. Notice that Deep Learning (DL) can provide high-quality results for huge amount of data and complex problems. In this sense, we employed DL for early prediction of students’ performance using data collected in the very first two weeks from introductory programming courses offered for a total of 2058 students during 6 semesters (longitudinal study). We compared our results with the state-of-the-art, an Evolutionary Algorithm (EA) that automatic creates and optimises machine learning pipelines. Our DL model achieved an average accuracy of 82.5%, which is statistically superior to the model constructed and optimised by the EA (p-value << 0.05 even with Bonferroni correction). In addition, we also adapted the DL model in a stacking ensemble for continuous prediction purposes. As a result, our regression model explained ~62% of the final grade variance. In closing, we also provide results on the interpretation of our regression model to understand the leading factors of success and failure in introductory programming.

Comparison of E-Learning, M-Learning and Game-based Learning in Programming Education – A Gendered Analysis

Learning to code is considered as a difficult and challenging task for a significant number of novice programmers in programming education. Novice programmers have to acquire different skills such as problem solving, program design, comprehension, and debugging at the same time. On the other hand, most introductory programming courses focus more on syntax of the programming language. In this study, we developed and introduced a ‘PROBSOL’ application in three different learning systems (E-learning, M-learning and Game-based learning) to enhance the problem solving skills of novice programmers in an introductory programming (IP) course. A survey was conducted with the IP students to determine their perception about all the three applications in the IP course. Gender differences were determined by comparing both female and male students’ responses for each question in the survey. The results of comparison show that male students were more satisfied with all the three applications compared to female students. Both female and male students perceived that all the three applications are user-friendly, enabled them to accomplish tasks more quickly, and enhanced their learning productivity. Overall, both male and female students appreciated all the three applications in the teaching and learning process of the IP course. This study implies that instructors can also use all the three applications as an additional teaching tool in the teaching and learning process of programming education.

READING SKILLS CAN PREDICT THE PROGRAMMING PERFORMANCE OF NOVICES: AN EYE-TRACKING STUDY

Due to the character of programming languages, reading ability may have more impact on learning to program than on learning in other subjects. This paper describes an exploratory study of the relationship between reading skills, as perceived through eye tracking, and the ability to program. An empirical investigation into this relationship determined that students with inadequate reading skills are at risk of failing at introductory programming. As an explanation for the effect of reading ability on learning to program, we argue that a programming language is a special high-level written language and that using it requires high levels of comprehension, inferencing, selective attention, organising and reflecting. As a result, a student’s reading ability will have a considerable effect on learning to program. Lack of reading skills may therefore be a factor that affect students’ ability to learn to program. Eye tracking can expose reading skills and, therefore, be used to identify at-risk introductory programming students. The practical contribution of this research is the demonstration of how eye tracking can reveal reading problems among programming students. We relate these reading problems to their programming performance, providing a theoretical account of the connection. The results suggest that efforts to improve reading skills could have a positive impact on learning to program.

Do Badges Affect Intrinsic Motivation in Introductory Programming Students?

Background. Programming is a challenging and highly important topic for introducing learners to our digital world. Research has shown that motivation plays a key role in programming performance. Gamification using digital badges has the potential to influence motivation, provide social recognition and encourage learner participation. More research is recommended to evaluate its motivational impact in different contexts. Intervention. This research explores the effects of badges on the intrinsic motivation levels of introductory programming students within a higher education institution. The course is offered during the first year of the programme. We report the results of a baseline study without badges and four subsequent badge experiments of different designs over a four-year period. Methods. This quasi-experimental study followed a pre-test/post-test design to measure the effects of badges on the intrinsic motivation levels of university-level introductory programming students. Badges were designed and implemented. Feedback via focus groups and a post-badge survey was collected. Results. Findings are inconclusive as the quantitative results suggest that badges did not increase intrinsic motivation scores. Contrastingly, badge survey and qualitative data indicate that badges were received more positively on average. Discussion. We analyse and discuss the results within the context of motivation and the programming discipline, and discuss external factors that may impact the relationship between gamification and motivation. Conclusion. Further research is necessary to investigate whether gamification, through the use of digital badges, can foster positive intrinsic motivational results, particularly in the well-known challenging domain of introductory programming.

Effect of Self-efficacy and Emotional Engagement on Introductory Programming Students

High failure rates appear to be a norm in introductory programming courses. Many solutions have been proposed to improve the high failure rates. Surprisingly, these solutions have not lead to significant improvements in the performance of students in introductory programming courses. In this study, the relationship between self-efficacy, emotional engagement and the performance of students in introductory programming courses were examined. Enjoyment, interest, and gratification were identified as three factors contributing to emotional engagement in introductory programming courses from a review of existing literature and from focus groups. An online survey of 433 students in introductory programming courses showed that the students’ programming self-efficacy beliefs had a strong positive effect on enjoyment, while gratification and interest had a negative effect on programming performance. These findings have implications for course instructors who design and deliver introductory programming courses.

Influência dos enunciados na resolução de problemas de programação introdutória

O método de ensino mais utilizado, em disciplinas de programação introdutória, é a proposição de problemas em que apresenta-se um enunciado com um problema descrito e os estudantes elaboram um algoritmo para solucioná-lo. Muitas são as dificuldades apresentadas pelos estudantes, principalmente relacionadas à compreensão e interpretação do enunciado. Esta pesquisa analisou os enunciados apresentados nos livros didáticos mais frequentemente adotados em universidades brasileiras, e constatou que geralmente são objetivos, sem indícios do processo de resolução, sem exemplificação e com um contexto predominantemente matemático. Nesse cenário formulou-se a questão de pesquisa: a estrutura e/ou o contexto de um enunciado podem influenciar o desempenho dos alunos, de programação introdutória na resolução de problemas? A estrutura está relacionada aos elementos que constam no enunciado para auxiliar o estudante a compreendê-lo tais como exemplos, casos de testes ou indícios da solução. O contexto se refere ao tema/enredo da questão. Partiu-se da crença de que em contextos que o estudante possui maior familiaridade, como jogos, compreenderá melhor os problemas e poderá ter melhor desempenho. Para responder esta questão realizou-se uma pesquisa experimental para avaliar a influência dos enunciados no desempenho dos estudantes ao resolverem problemas de programação introdutória. Foram propostos problemas usando dois contextos: matemático e jogos e dois tipos de estrutura: estruturado e não estruturado formando assim quatro grupos de tratamento. No experimento participaram 246 estudantes de oito turmas de seis instituições de ensino superior de três diferentes estados de diferentes regiões geográficas do Brasil. Os resultados apontaram que os estudantes tiveram melhor desempenho quando os enunciados são estruturados e que este é acentuado quando o contexto é matemático. Não foi encontrada nenhuma evidência de que a utilização do contexto de jogos nos enunciados favoreceu o desempenho. O pior desempenho ocorreu o grupo de questões do contexto matemático não estruturado, justamente o modelo de enunciado mais frequentemente encontrado nos livros didáticos, o que leva a conclusão de que é necessário repensar a forma de apresentar os problemas aos estudantes de programação introdutória.

The Impact of Lecture Attendance on Exams for Novice Programming Students

In this paper, the correlation between lecture attendance and assessment tasks on final exam performance of introductory programming students has been analyzed to identify if lecture attendance, and completion of in-class and take home formative assessment tasks affects student performance in the final examination. In this study, only lecture attendance, homework exercises and class demonstration scores, and final exam marks have been considered. This study used Spearman's Rank correlation coefficient and multiple regression techniques via SPSS software to analyze the student data of the academic years 2012, 2013 and 2014 of an introductory programming course to test the hypotheses. It is found that, there is a significant correlation between homework exercises and final exam scores. However, formal lecture attendance and final exam performance were negatively correlated. Moreover, multiple regression results of assessment tasks such as homework exercises, class activities and lecture attendance on final exam scores, did not provide any significant value to support the statement Marks achieved in homework, class demonstrations, and lecture attendance, have a significant positive impact on final examination results.

A model for teaching an introductory programming course using ADRI

High failure and drop-out rates from introductory programming courses continue to be of significant concern to computer science disciplines despite extensive research attempting to address the issue. In this study, we include the three entities of the didactic triangle, instructors, students and curriculum, to explore the learning difficulties that students encounter when studying introductory programming. We first explore students' perceptions of the barriers and affordances to learning programming. A survey is conducted with introductory programming students to get their feedback on the topics and associated learning resources in the introductory programming course. The instructors' perceptions are included by analyzing current teaching materials and assessment tools used in the course. As a result, an ADRI based approach is proposed to address the problems identified in the teaching and learning processes of an introductory programming course.

Developing an Educational Game to support Cognitive Learning

This paper outlines how an educational game can be used to support the learning of programming within the Computer Science (CS) discipline and reports on the qualitative results of a series of rigorous studies conducted through using this game on first year introductory programming students. Although this paper applies to the CS discipline computational thinking (CT) is an intrinsic part of the games process applicable to any discipline. This is because CT is a problem solving approach which combines logical thinking with CS concepts to produce a recipe for solving problems in any discipline regardless of where the problem lies.

Going SOLO to assess novice programmers

This paper explores the programming knowledge of novices using Biggs' SOLO taxonomy. It builds on previous work of Lister et al. (2006) and addresses some of the criticisms of that work. The research was conducted by studying the exam scripts for 120 introductory programming students, in which three specific questions were analyzed using the SOLO taxonomy. The study reports the following four findings: when the instruction to students used by Lister et al. - "In plain English, explain what the following segment of Java code does" - is replaced with a less ambiguous instruction, many students still provide multistructural responses; students are relatively consistent in the SOLO level of their answers; student responses on SOLO reading tasks correlate positively with performance on writing tasks; postgraduates students manifest a higher level of thinking than undergraduates.

Engaging students to work with self-assessment questions

We explored two approaches for encouraging introductory programming students to use the web-based, self-assessment system, QuizPACK. An "organizational" approach applied specially constructed classroom quizzes, while the "technical" approach introduced adaptive guidance. Our studies demonstrated that each of these caused a dramatic increase in system use. This approach could be useful in many other contexts, when an educationally beneficial system is underused by students.

Engaging Introductory Programming Students with CGI

The technical component of Management Information Systems (MIS) programs can be challenging to design. Unlike computer science students, MIS majors tend to take relatively few technical courses, yet are expected to graduate with a broad array of computer skills. To meet these expectations, foundation courses are often designed to serve multiple objectives. For example, as a first course in an upper division undergraduate MIS major, the author teaches an introductory programming course in the C++ language. Beyond teaching the basic elements of programming and computer architecture, that course is expected to explore data representation (a foundation for data communications), the file-handling concepts (the building block of databases), and basic application construction (a core concept of systems analysis and design). To meet these multiple objectives, programming courses need to limit the number of language features introduced. A particularly common target for simplification is input and output (I/O). The development of a graphic user interface is quite complex and text-based (console) I/O is sufficient to teach most programming concepts. Unfortunately, limiting I/O in this fashion also leads to programs that appear dated by today’s standards. In consequence, students can easily develop the perception that programming is a wholly uninteresting activity, unworthy of serious consideration as a career. To counteract such a perception, exercises need to be provided that engage students in the programming process and demonstrate its potential. In this vein, one class of exercises that we have developed allows the student to write programs that interact with a Web browser. Such exercises can be easy to construct and utilize the same console I/O that students have been taught. In addition, these exercises introduce key data communication concepts (e.g., HTML) and demonstrate clientserver design. In this brief, an example of such an exercise is described.

Ways of Experiencing the Act of Learning to Program: A Phenomenographic Study of Introductory Programming Students at University

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A special learning environment for repeat students

In 1997, surveys of a group of introductory programming students, in a class with a predominance of repeat students (i.e., students who had previously failed the subject), provided an opportunity to establish a profile of the weakest students. These students were the "alienated" ones who had not wanted to do this course in the first place, had little motivation to learn programming, and were characterised by poor class attendance and low work output. In 1998 a new learning environment, tailored to these students' special needs, was implemented to encourage them to achieve success. Improvement was observed in many aspects of the learning behaviour of these students.

Knowledge Integration in Introductory Programming: CodeProbe and Interactive Case Studies

Abstract To help introductory programming students gain an integrated, generative understanding of LISP, we designed, implemented, and evaluated the LISP Knowledge Integration Environment (LISP‐KIE). The LISP‐KIE reflected a conceptual framework which featured (a) scaffolding of students as they control their own learning rather than telling students what they should know and (b) activities engaging students in expert problem‐solving practices rather than exercises emphasizing syntax and small problems. We conducted two in‐depth studies and one comparison study to show that the LISP‐KIE fostered knowledge integration. By knowledge integration, we mean linked, organized, and connected information about such aspects of programming as design, testing, specific problem solutions, and self‐monitoring.