Exploring the Difficulty of Faded Parsons Problems for Programming Education

Lecture recordings are a common and useful resource for students due to the flexibility they provide. Recent rapid shifts to online modes of teaching have made recorded lectures especially valuable as many students rely on them to access course content. As a result, there is a pressing need to understand how students consume lecture content via recordings and what patterns of access are effective. In this research, we investigate the common lecture recording viewing behaviors of students and the relationship between lecture recording viewing and academic performance in a first-year programming course. Several trends were observed. A significant positive correlation between lecture recording views and final grades was identified. Students who repeated the course after failing it once, achieved, on average, higher grades if they had more lecture recording views in their second attempt. A small number of students engaged in habitual “binge-watching” behavior and those students had lower grades, on average, than students who watched more regularly. This was a particular problem for repeating students, attempting the course a second time, who failed the course at twice the rate if they engaged in habitual binge-watching. Although lecture recordings appear to be a helpful learning resource for students in introductory programming courses, this work suggests that binge-watching is an unproductive study strategy that should be discouraged.

Recent research has demonstrated pair programming to be an effective model of collaborative learning for millennial students. However, much of the research describes the impact of pair programming in first-year programming courses. This paper highlights experiences using pair programming in an advanced web development programming course. Most of the students in the course were at the junior or senior level and had not been formally introduced to pair programming prior to taking the course. Qualitative data were collected through the use of written reports and surveys. The author discusses what was learned about the impact on students’ attitudes, learning and quality of work. Challenges are also described, as well as recommendations for enhancements.

Asking questions in class in front of peers can be intimidating for many students. However, receiving timely answers to questions can help students better understand subsequent material. Moreover, prior work has shown that students learn more effectively in interactive classroom environments that promote instructional practices such as question posing. This paper describes a web-based platform, HandsUp, that addresses the underlying factors preventing students from asking questions in lectures. Using this tool, students can ask questions of their instructor while remaining anonymous to their peers, and instructors can choose to answer the questions that are of interest to the most students. We find that students can interact with the tool easily, and we present a short case study of its use in a large first-year programming course.

The recent emergence of code generation tools powered by large language models has attracted wide attention. Models such as OpenAI Codex can take natural language problem descriptions as input and generate highly accurate source code solutions, with potentially significant implications for computing education. Given the many complexities that students face when learning to write code, they may quickly become reliant on such tools without properly understanding the underlying concepts. One popular approach for scaffolding the code writing process is to use Parsons problems, which present solution lines of code in a scrambled order. These remove the complexities of low-level syntax, and allow students to focus on algorithmic and design-level problem solving. It is unclear how well code generation models can be applied to solve Parsons problems, given the mechanics of these models and prior evidence that they underperform when problems include specific restrictions. In this paper, we explore the performance of the Codex model for solving Parsons problems over various prompt variations. Using a corpus of Parsons problems we sourced from the computing education literature, we find that Codex successfully reorders the problem blocks about half of the time, a much lower rate of success when compared to prior work on more free-form programming tasks. Regarding prompts, we find that small variations in prompting have a noticeable effect on model performance, although the effect is not as pronounced as between different problems.

Finding errors in the source code is a typical kinds of test in the programming courses, which is helpful to assess the students' ability in program comprehension and debugging. In this paper, we propose an analysis scheme to interpret the measured line-level eye movement in an error-finding test of C language. An eye-tracking measurement system is implemented to collect the student's eye movement; during the test, the students select the error lines by mouse click in the web pages. We divide the students' eye movement into multiple cognitive tasks according to their decision actions, i.e. the mouse click events. For each cognitive task, we formulate the line-level program execution sequence around the code line selected by the students. A new metric, namely Matched Movement Ratio (MMR), is proposed to describe the proportion of line-level eye-focus jumping events that matches with the program execution sequence. We validate the calculation of MMR by two case studies, and further utilize this metric to conduct group study for 19 students in a test about bubble-sorting algorithm. Experiment results show that, MMR can differentiate the students by their code tracing performance in error-finding missions. Although our scheme can not infer the whole cognitive process in test, MMR can work as a reference quantifying the students' cognitive efforts tracing the code lines. Our results provide evidences for the teacher to diagnose the weakness of students and provide improvement suggestions in programming courses.

This research paper describes the use of peer review to improve information literacy. Peer-reviewed assignments for learning have been seen favorably within the literature. The articulated benefits range from students feeling more engaged, having expressed less anxiety, or found to be better equipped to perform in unfamiliar areas outside their current learning environments. However, minimal research examines the benefits specifically for the feedback provider (reviewer) when a more modern tool, such as the Canvas Learning Management System (LMS) is used. During the fall 2015 semester, a study was conducted to examine the peer review process from the vantage point of the reviewer when mitigated by an LMS. Since peer review is seen as a social activity, this study is guided by a social constructivism teaching framework to investigate peer review activities for (a) linear relationships to that of a perceived social element inclusion, (b) changes in learning from the perspective of the reviewer rather than the receiver of feedback, and (c) improvement in perceived information literacy. Additionally, this research examines Canvas attributes as identified by Sondergaard & Mulder [1] (2012) of (a) Automation, (b) Simplicity, (c) Customizability, and (d) Accessibility, which support statements from the literature that indicate a lack of investigation of more modern peer review tools. Survey results, both qualitative and quantitative, were analyzed across three different peer-reviewed assignments for this examination. Of the 91 respondents, representing a 32% response rate, descriptive analysis revealed themes ranging from Changes in Student Efforts to Valued New Perspectives; whereas, expected Active Learning and Social Benefits slightly contradicted the positive tone that was originally found in the thematic review. Overwhelming positive ratings were collected regarding the use of the LMS to support and implement a peer-reviewed assignment. Perceived affects upon the peer reviewer, and how these types of assignments can support the proposed ABET General Criterion 3 Student Outcomes and General Criterion 5 Curriculum currently under revision are discussed. Lastly, these data are represented for use as an evaluation baseline for future planned investigations and for other faculty and course developers, who are considering implementation of peer-reviewed activities within first-year program courses.

The use of technology integration is the way of innovation in today’s world-class learning. Technology integration is a combination of technologies such as computers, mobile devices like smartphones and tablets, digital cameras, the internet, and more in the practice of daily lecture sessions. Technology integration could help the process of learning especially for courses that considered as tough by the students. Therefore, educators need to be aware of the choice of methods or approaches so that teaching and learning are conducted in meaningful ways. Programming courses are compulsory for students in Faculty of Information Sciences and Technology, National University of Malaysia. However, some students find it difficult to excel in programming courses. In this study, technology integration in learning programming courses challenges the limitations of student opportunities in solving real problems lead to inconsistently use of the expertise and skills. In addition, the challenge of learning programming leads students to generate rote learning. Hence, technology integration in learning programming should be appropriate with the application of technology and applying meaningful learning so that the technology integration will be effective and meaningful. This study is conducted to propose and verify a technology integration framework for learning programming courses. Stratified Random Sampling through quantitative study method is used which involving 109 respondents. Quantitative data are analyzed using multiple linear regression method. Based on previous studies, five factors have been identified namely learning technology, learning competence, technology implementation, meaningful learning and contextual learning that would affect students’ desire to learn programming courses. The results discover that all the factors have significant relationships in influencing the desire to learn programming courses among undergraduate students for the faculty. This study is expected to assist educators and administrators to apply and improve the use of technology integration in meaningful learning for programming courses.

Learning computer programming has become an essential skill in the digital age, presenting significant challenges and opportunities for students. This study examined the levels of motivation and perceived self-efficacy as factors in the initial learning of computer programming and their possible correlation with the academic performance of Computer Science students at a university in Puerto Rico. The approach was quantitative, using a survey research design (cross-sectional), with a self-administered online questionnaire. Evidence of validity related to content, response process, and internal structure was collected, and a non-probability convenience sampling was employed. The data were processed using the SPSS statistical package. The results showed a significant positive Spearman correlation between the items of the self-efficacy and motivation subscales with the academic performance reported by the participants in the introductory programming course. The study concluded that the self-efficacy and motivation of programming learners positively affect academic performance, contributing to the development of higher-order thinking skills such as problem-solving and creativity, highlighting them as fundamental factors in the initial learning of computer programming.

Learning to create well-designed and robust Java programs requires, besides a good understanding of the language, a significant amount of practice. In this paper we present the JavaFest, a collaborative learning technique for teaching Java to beginning programmers. A JavaFest is a group exercise that instructors can add to their repertoire of teaching techniques. It provides an opportunity for students to practice programming in a motivating but non-threatening environment, and to learn from the experience of their peers. Moreover, a JavaFest allows the instructor to gain insight into the current standing of the students in her class.We describe the concept of a JavaFest and present three case studies in the form of three concrete JavaFests we developed and evaluated in our own object-oriented programming course. The general idea of a JavaFest, and the three specific examples we describe and evaluate, can easily be adopted to enhance any Java programming course.

Six Steps for Cultivating Successful Undergraduate Research

Computer programming is now increasingly becoming a compulsory subject at the high school level. The main purpose of the introduction of programming languages at this stage is to develop logic and reasoning skills that may help students in their ordinary activities. Pakistani schools have also started introducing computer programming at the high school level. GWBasic and C are two major languages being used to teach this introductory course. This paper presents the difficulties faced by the students to learn programming languages in the high schools of Pakistan while learning in any of these two languages. To this end, the content of the course has been divided into three difficulty levels. A survey based approach has been employed to get useful data from the students who have been taught this course in either of the aforementioned languages. A detailed questionnaire has been created and is filled by the student to express the ease of learning for different concepts. The collected data enables us to perform a retrospective analysis to figure out as to which language offers a smoother and easier learning curve at a given level. The results show that GWBasic is relatively easier language for the students to learn introductory course in computer programming. The accumulated data also reveals that the students struggle to learn advanced concepts that invites for a revision of curriculum or pedagogical practices being followed to teach this course.

The emergence and rapid spread of COVID-19 changed the face of education.At Michigan Technological University (Michigan Tech) , planning for the Fall 2020 semester started well before the end of the 2019-20 academic year.For the Fall 2020 semester, faculty at our university had the option to teach in various modalities according to what fit their personal and course needs.The options included online (asynchronous materials completed with time and place flexibility), remote (synchronous, scheduled meetings that students can attend virtually), or hybrid (classes that have face-to-face meeting times, but offer students opportunities to complete most activities virtually and/or remotely).Restrictions placed on class size with physical distancing measures limited the number of students who could attend a given class session face-to-face.In the first-year program at Michigan Tech, we value an active, collaborative learning environment; an environment that would be difficult to implement asynchronously.Despite the shift to a remote or hybrid modality, we wanted our first-year students to still experience an active, collaborative learning environment.In this paper, we focus on discussing the steps we took to maintain and/or improve the connection between students and the engagement with the course materials.A comparison of responses from surveys administered in the first-semester engineering course at Michigan Technological University indicates that students were at least as satisfied or more satisfied with the remote and hybrid versions in Fall 2020 than the traditional face-to-face version in Fall 2019.Specifically, a greater percentage of students enjoyed the course, felt engaged and valued, were more prepared for lessons and saw value in the course and the skills they learned in the course.

To perform a number of tasks such as inferring design rationale from past code changes or assessing developer expertise for a software feature or bug, the evolution of a set of lines of code can be assessed by mining software histories. However, determining the evolution of a set of lines of code is a manual and time consuming process. This paper presents a model of this process and an approach for automating it. We call this process History Slicing. We describe the process and options for generating a graph that links every line of code with its corresponding previous revision through the history of the software project. We then explain the method and options for utilizing this graph to determine the exact revisions that contain changes for the lines of interest and their exact position in each revision. Finally, we present some preliminary results which show initial evidence that our automated technique can be several orders of magnitude faster than the manual approach and require that developers examine up to two orders of magnitude less code in extracting such histories.

In this exploratory study, we analysed 396 drawings by first-year programming students in response to the question what does programming mean to you. We were surprised by the level of care that students gave to their drawings, and we were confronted by the degree of emotion contained within the drawings. To date, few studies have focused specifically on programming students' emotional reactions to their learning experiences. Here, we analysed our student drawings as 'group data', taking note of recurring artefacts, actors, activities, aspirations and affect across the entire dataset. The observed patterns noted in the drawings raised questions around how students conceptualise programming, both as a subject and potential future profession. As contributions to the field, we: (1) discuss the potential of drawing as a research methodology for computer science; (2) present our findings and observations; and (3) suggest how this type of data could be used to better inform teaching practice in novice programming courses.

Writing research reports at the undergraduate level is one of the obligations that must be fulfilled by students as a fulfillment of graduation requirements at a university. One of the independent learning programs implemented at Nusa Putra University is through the research method, where students are required to conduct research as a graduation requirement in the Study Completion Program course. The growing development of information and communication technology provides opportunities for students to determine research themes. However, sometimes students take research themes that are not in accordance with the concentration in the study program. This research was conducted with the aim of identifying how the LDA topic modeling method can analyze research topic trends by modeling topics on research titles that have been taken by students at the Informatics Engineering Study Program, University of Nusa Putra. Latent Dirichlet Allocation (LDA) is one of the most popular topic modeling methods today. This research uses a dataset in the form of 159 titles of study completion program research reports and tittles of final assignment reports for students of the Informatics Engineering study program, University of Nusa Putra. This research is expected to be a reference in conducting research by students based on the topics that have been modeled