Introductory Programming Research Articles

The Comparison of Students’ Self-Assessment, Gender, and Programming-Oriented Spreadsheet Skills

Previous research proved that teaching spreadsheeting from a programming perspective is much more effective than the widely accepted tool-centered surface approach methods. Spreadsheeting as an introductory programming approach allows students to build up schemata leading to contextualized, concept-based problem-solving. Furthermore, it provides tools for real-world problem-solving in other disciplines, and supports knowledge-transfer to database management and “serious” programming. The present study provides the details of a nationwide testing of Grades 7–10 students on how they evaluate their spreadsheet knowledge, which classroom activities form their self-assessment values, and the results of three spreadsheet tasks evaluated by the SOLO categories of understanding. The comparison reveals that most students’ spreadsheet knowledge is pre-structural. On the other hand, they assess themselves much higher, which is primarily based on the number of activities carried out in classes. Traces of conscious problem-solving and knowledge-transfer within the scope of spreadsheeting are hardly detectable, while knowledge brought from mathematics is recognizable. In general, we found proof that the pieces of knowledge remain unconnected, not allowing students to reach the relational level of understanding and build up long-lasting knowledge.

A Guided Scratch Visual Execution Environment to Introduce Programming Concepts to CS1 Students

First-year computer science (CS1) university students traditionally have difficulties understanding how to program. This paper describes research introducing CS1 students to programming concepts using a Scratch programming language guided visual execution environment (VEE). The concepts addressed are those from an introductory programming course (sequences, variables, operators, conditionals, loops, and events and parallelism). The VEE guides novice students through programming concepts, explaining and guiding interactive exercises executed in Scratch by using metaphors and serious games. The objective of this study is, firstly, to investigate if a cohort of 124 CS1 students, from three distinct groups, studying at the same university, are able to improve their programming skills guided by the VEE. Secondly, is the improvement different for various programming concepts? All the CS1 students were taught the module by the same tutor in four 2-h sessions (8 h), and a qualitative research approach was adopted. The results show students significantly improved their programming knowledge, and this improvement is significant for all the programming concepts, although greater for certain concepts such as operators, conditionals, and loops than others. It also shows that students lacked initial knowledge of events and parallelism, though most had used Scratch during their high school years. The sequence concept was the most popular concept known to them. A collateral finding in this study is how the students’ previous knowledge and learning gaps affected grades they required to access and begin study at the university level.

How Technologies Assisted Science Learning at Home During the COVID-19 Pandemic.

As most other aspects of life, education was strongly affected by the lockdowns imposed to slow down the spread of the COVID-19 pandemic. Teachers at all levels of education suddenly faced the challenge of adapting their courses to online versions. This posed various problems, from the pedagogical and psychological components of having to teach and learn online to the technical problems of internet connectivity and especially of rethinking hands-on activities. The latter point was especially important for subjects who involve very practical learning, for which teachers had to find out alternative activities that the students could carry out at home. In the subjects dealing with natural sciences, impaired access to instrumentation and reagents was a major limitation, but the community turned out very resourceful. Here I demonstrate this resourcefulness for the case of undergraduate chemistry and biology courses, focusing on how do-it-yourself open technologies, smartphone-based instruments and simulations, at-home chemistry with household reagents, online video material, and introductory programming and bioinformatics, which helped to overcome these difficult times and likely even shape the future of science education.

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.

Enhancing problem‐solving skills of novice programmers in an introductory programming course

Enhancing problem‐solving skills of novice programmers in an introductory programming course

Applying Cognitive Load Theory to Examine STEM Undergraduate Students’ Experiences in An Adaptive Learning Environment: A Mixed-Methods Study

This study examined undergraduate STEM students’ experiences using an online introductory computer programming learning environment equipped with an automated hint generation system. Following a convergent parallel mixed methods design, this study utilized both quantitative and qualitative data from student experiential data. Analysis by level of prior knowledge demonstrated that elements of the learning environment did not cater to their learning needs and cognitive architecture. Cognitive Load Theory was used to contextualize system elements against both higher and lower prior experience learners, ultimately pointing to a need to design better scaffolds and hints to the needs of novice CS learners.

Early Prediction for At-Risk Students in an Introductory Programming Course Based on Student Self-Efficacy

Data Mining is a growing field, a strand of which is Educational data mining (EDM). EDM is currently used to help institutions and students through creating accurate predictions that are considered in decision making. One of EDM’s concerns is that of predicting students’ academic performance and fundamental learning difficulties in a particular course. In fact, EDM can help computer science (CS)-enrolled students to predict whether they can pass their courses without taking further action. An introductory programming course is usually the first challenging course faced by students in CS departments since a student’s performance in such a course is highly based on their intellectual skills. This paper presents a real case study from one of Saudi Arabia’s leading universities. This study used well-known prediction models— specifically, decision tree (DT), k-nearest neighbor (kNN), Naïve Bayes (NB), and support vector machine (SVM) models—to create a reliable prediction model for at-risk students in an introductory programming course using preliminary performance information showing their self-efficacy. The results of this study showed that the DT and SVM models yielded the best performance with the highest accuracy rate (99.18%). Furthermore, comparisons between the applied models were conducted with different evaluation metrics.

The Effectiveness of a Brief Mindfulness-Based Program for Social Work Students in Two Separate Modules: Traditional and Online

ABSTRACT Purpose This study aimed to design a brief mindfulness-based training program for social work students and examine its effectiveness and working mechanisms. Method The study used a quantitative approach to examine the program’s effectiveness for 101 undergraduate social work students in two separate modules (traditional classroom-based and online). Results One-way analysis of covariance revealed statistically significant reductions in depression, anxiety, stress, and rumination, and improvements in self-compassion and mindfulness among the intervention groups compared to the waitlist control groups. Mediation analyses showed that mindfulness, rumination, and self-compassion were mediators of the intervention effects. Discussion The brief mindfulness program can be used as an effective and introductory mindfulness program for undergraduate social work students in either classroom-based or online modules. Alternations in mindfulness, rumination, and self-compassion can be considered as possible working mechanisms.

Introductory programming and young learners with visual disabilities: a review

Introductory programming and young learners with visual disabilities: a review

How Early Is Early Enough: Correlating Student Performance With Final Grades

Student retention is one of the greatest challenges facing computer science programs. Difficulties in an introductory programming class often snowball, resulting in poor student performance or dropping the major completely. In this paper, we present an analysis of 197 students over 6 semesters from 11 sections of an introductory programming class at a private four-year liberal arts university in the southeastern United States. The goal of this research was to find the earliest point in the assessment sequence which could predict final grade outcomes. Accordingly, we measured the degree of correlation between student performance on quizzes, labs, programs, and tests compared to final course grade. Overall, the results show a strong positive correlation for all four assessment modalities. These results hold significance for educators and researchers insofar as the body of computing education research is extended by evaluating the relative effectiveness of early semester subsets of each of the four categories of student data to model class outcomes.

Using flipped classroom and peer instruction methodologies to improve introductory computer programming courses

Learning to write computer programs and engaging students in introductory programming subjects are difficult tasks. This study presents the results obtained when using flipped classroom and peer instruction methodologies in an introductory course of programming. Before the lecture, out-of-class study and on-line homework questionnaires were applied, and peer instruction was used in the classroom to encourage students' participation and discussion, assisted by an on-the-fly assessment app. The main academic results, the degree of involvement in the course activities, and the students' feedback were collected and compared with similar data from previous academic years. Significantly better pass (χ2 = 12.94, p < .001) and dropout rates (χ2 = 7.08, p < .01) were obtained when using flipped classroom and peer instruction. Laboratory attendance also improved significantly (χ2 = 27.62, p < .001). Our results showed significant positive correlations between the work performed at home and the grade obtained in the final exam (ρ = 0.51, p < .001). According to the students' opinions, class preparation at home increased significantly (χ2 = 46.59, p < .001) by 33% due to the new methodologies used. These results, based on a sample of six offerings of the same programming course, suggest that the application of flipped classroom and peer instruction improves the quality of the autonomous work of the students as well as their involvement in the lectures, and therefore, their knowledge acquisition improves.

Teaching and Learning to Program: Umbrella Review of Introductory Programming in Higher Education

Introductory programming courses in science, technology, engineering, and mathematics (STEM) degrees are critical to student success throughout the students’ academic and professional route but have traditional failure and dropout rates. The number of publications and reviews on the subject is growing, so we realize the need to prepare an umbrella review, or review of reviews, to group previous studies and extract more comprehensive and ambitious results. Based on the databases ACM, Google Scholar, IEEE, SCOPUS and Web of Science libraries, a formal search was created that resulted in 21 reviews on programming fundamentals in higher education context. Results include bibliometric information on the CS1 reviews, in the context of higher education (namely annual evolution, number and information on authors, types and sources of information, countries of affiliation, languages, keywords and most cited articles), the purpose of the reviews and research questions, methods (namely search strategy, databases used, eligibility criteria) and results (number of records and tables or divisions were made to catalog the articles). We present a taxonomy with four different types of purpose: general, specific, student group and teacher directed. We found very interesting catalogs that can serve as a tool for future work, whether by researchers in the field or by authors who intend to carry out reviews related to introduction to programming, especially in the context of higher education.

Introductory programming course: review and future implications.

The introductory programming course (IPC) holds a special significance in computing disciplines as this course serves as a prerequisite for studying the higher level courses. Students generally face difficulties during their initial stages of learning how to program. Continuous efforts are being made to examine this course for identifying potential improvements. This article presents the review of the state-of-the-art research exploring various components of IPC by examining sixty-six articles published between 2014 and 2020 in well-reputed research venues. The results reveal that several useful methods have been proposed to support teaching and learning in IPC. Moreover, the research in IPC presented useful ways to conduct assessments, and also demonstrated different techniques to examine improvements in the IPC contents. In addition, a variety of tools are evaluated to support the related course processes. Apart from the aforementioned facets, this research explores other interesting dimensions of IPC, such as collaborative learning, cognitive assessments, and performance predictions. In addition to reviewing the recent advancements in IPC, this study proposes a new taxonomy of IPC research dimensions. Furthermore, based on the successful practices that are listed in the literature, some useful guidelines and advices for instructors have also been reported in this article. Lastly, this review presents some pertinent open research issues to highlight the future dimensions for IPC researchers.

Strangers everywhere? Home and unhomeliness in newly arrived pupils’ narratives on exile

ABSTRACT This article scrutinises the ways in which pupils who have experienced transnational migration construct ‘home’ and the unmaking of ‘home’. Researchers have argued that migrants’ perspectives on belonging are seldom granted scholarly attention. Here, we seek to redress this oversight by inquiring about the ways in which newly arrived migrants define their (un)homeliness in Sweden in the context of astate-sponsored introductory language programme. The focus is on how these pupils themselves define the notion of home, their sense of belonging, and what they envision as necessary to achieve in order to become part of the national community. What emerges in these stories is aconstant negotiation to fill the idea of ‘home’ with content. These negotiations take place in apresent, but always in relation to both apast and an imagined future– in which homeliness appears in different ways, with different meanings.

Comparison of C++ and Java in Implementing Introductory Programming Algorithms

Computer programming is the heart of computer science and C++ and Java are the most popular and widely used languages. The performance of C++ and Java programming languages has been benchmarked using robotics, numerical, genetic and evolutionary algorithms, but not using introductory programming algorithms. This article examined C++ and Java by analysing the implementation of novice algorithms of introductory programming courses by evaluating the difficulty, effort, time and delivered bugs of programs with Halstead software metrics. The study identified that Java is more difficult than C++ in the implementation of selected algorithms. Similarly, the efforts required to translate the novice algorithms in Java are higher than C++. The time involved in translating selected algorithms in C++ is lower than Java. Similarly, the number of delivered bugs in C++ is lower than Java. The study suggests that C++ is more suitable than Java for the implementation of introductory programming algorithms and reasonably more suitable for introductory programming courses. The study emboldens the programming linguists to do further analyses in contemplating other programming languages with Halstead software metrics and other kinds of algorithms.

Computational skills by stealth in introductory data science teaching

AbstractIn 2010, Nolan and Temple Lang proposed “integration of computing concepts into statistics curricula at all levels.” The unprecedented growth in data and emphasis on data science has provided an impetus to finally realizing full implementations of this in new statistics and data science programs and courses. We discuss a proposal for the stealth development of computational skills in students' exposure to introductory data science through careful, scaffolded exposure to computation and its power. Our intent is to support students, regardless of interest and self‐efficacy in coding, in becoming data‐driven learners, who are capable of asking complex questions about the world around them, and then answering those questions through the use of data‐driven inquiry. Reference is made to the computer science and statistics consensus curriculum frameworks the International Data Science in Schools Project (IDSSP) recently published for secondary school data science or introductory tertiary programs, designed to optimize data‐science accessibility.

Brief introductory group education programs for chronic disease patients in chronic disease management: a scoping review protocol.

This review will scope the literature and map the features of brief introductory group education programs implemented in chronic disease management. Brief introductory group education programs are resource-efficient interventions used in chronic disease management to educate patients about basic disease concepts, self-management strategies, and to introduce specialist services. There is a lack of published research that synthesizes the characteristics, guiding principles, and outcomes reported in brief group education programs in chronic disease management. This scoping review will seek to identify brief introductory group education programs and describe the i) scope of literature available on such programs, ii) characteristics of the programs, iii) guiding self-management principles used and the extent to which programs follow such principles, and iv) types of outcomes reported. This review will consider studies describing an introductory or brief group patient education program (one to four sessions, no more than eight hours) for the management of chronic disease in adults with ongoing chronic disease. MEDLINE, Scopus, CINAHL, Emcare, Web of Science, and PsycINFO will be searched for English-language articles published from 2001 to the present. Titles and abstracts will be screened against inclusion/exclusion criteria, followed by full-text review, independently assessed by two reviewers. Eligible articles will be extracted and charted using a standardized data extraction form. A descriptive review to summarize and contextualize the extracted data will be conducted.

Self-evaluation Interventions: Impact on Self-efficacy and Performance in Introductory Programming

Research has repeatedly shown self-efficacy to be associated with course outcomes in CS and across other fields. CS education research has documented this and has developed CS-specific self-efficacy measurement instruments, but to date there have been only a few studies examining interventions intended to improve students’ self-efficacy in CS, and several types of self-efficacy interventions suggested by previous research remain to be tested in CS. This study attempts to address this lack of research by reporting on the results of a trial intervention intended to improve students’ self-efficacy in an introductory programming course. Students were recruited to complete a self-evaluation task, which previous research has suggested could have a beneficial impact on self-efficacy, which should in turn have a beneficial impact on course performance. Participating students’ course outcomes and self-efficacy were compared with those of the students who did not complete the self-evaluation task, using propensity score weighting adjustments to control for differences between the groups on entering characteristics and prior values of self-efficacy and course outcomes. We found that, whereas there was only marginal evidence for the self-evaluation intervention having a direct effect on self-efficacy, students who completed the self-evaluation task had significantly higher project scores during the weeks they were asked to complete it, compared to the students who did not participate. These findings suggest that there are potential benefits to incorporating self-evaluation tasks into introductory CS courses, although perhaps not by virtue of directly influencing self-efficacy.

Aligning and Assessing Teaching Approaches With SOLO Taxonomy in a Computer Programming Course

A teaching approach plays an important role in teaching and learning process of an introductory programming (IP) course. The teaching approach should focus on different programming skills required by novice programmers. In this study, we introduced the teaching and learning approach based on an ADRI (Approach, Deployment, Result, Improvement) approach in the IP course which focuses on both programming knowledge (syntax and semantics) and problem solving strategies. We compared the teaching and learning approach of the IP course with the five levels of SOLO taxonomy. We assessed the students’ performance by using different assessment tasks based on the four stages of the ADRI approach. Results show that the current teaching and learning approach of the IP course addressed all the five levels of SOLO taxonomy. The students’ performance in the Approach and Result stages (82%) are good, and the performance in the Improvement (71%) and Deployment (69%) stages are satisfactory. Overall, the ADRI approach provides positive impact on the teaching and learning process of the IP course.

Pelatihan Tata Kelola Webinar Bagi Pengurus dan Anggota UKK KSR PMI Unit Iain Pekalongan

Currently, technological sophistication brings new innovative ideas to educational activities. Webinars are a solution for the effective use of online learning media. Webinar governance training For administrators and members of the KSR PMI IAIN Pekalongan unit, it really needs to be delivered with an interesting method adapted to the Z generation of internet generation. This community service aims to provide assistance on webinar governance as an introductory program on How to conduct online webinars and to explore digital programs during the Covid 19 pandemic which consists of training on making registration landing pages, training on making certificates quickly and training in zoom governance. Carried out by training or training methods as well as live appearances to carry out online activities. The participants were very enthusiastic in carrying out the webinar governance training event which was shown by 40 participants or 100% of the participants were happy to take part in the management training event and the results of observations made by the service team also showed that almost all participants 87% (35 participants) were able create a registration landing page, able to create certificates and e-certificates quickly and be able to operationalize the zoom application.