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This small scale study aims to analyze the question papers of Board of Intermediate and Secondary Education in the subject of computer science with reference to item analysis and Bloom's taxonomy. Data were collected from 100 students of Grade 9th and 10th from the schools of Lahore city using convenient sampling technique. Data collected on the papers developed by Board of Intermediate and Secondary Education for the year of 2015 and 2016. Item analyses were performed using Conquest software. Findings of the study shows that in the question papers conducted by Board of Intermediate and Secondary Education the majority questions were measuring the student abilities of knowledge and comprehension and only few questions were given to measure the student abilities to analyze, synthesize and evaluate, and this can be very helpful for the policy makers. Result of item analysis shows that many questions were not in the acceptable range of item difficulty and item discrimination. Items in the question papers were either too easy or too difficult. Findings revealed that the papers conducted and administered by Board of Intermediate and Secondary Education were not up to the mark, with reference to Bloom's taxonomy. The researcher recommended to train the assessment committee/panel developing the items.

Faculty in the information systems (IS) and information technology (IT) fields are faced with the challenge to keep their curriculum relevant and current. What was taught two years ago will often be outdated and faculty must constantly update their curriculum on which courses should be taught as well as what should be taught within a particular course. This research continues a fifteen-year effort to help understand employer needs in terms of the skills they desire new hires to possess upon employment. This is the sixth version of this employer survey. The survey continues to report the responses of over 500 IS/IT professionals and was expanded to ask additional questions related to salary information. In addition, based on feedback from open-ended questions in a prior survey, new categories were added to the survey. Several key results and changes from prior surveys include that VR/AR (virtual reality/augmented reality) platforms showed the highest anticipated growth rate for all operating platforms in the next two years, analytics tools such as Apache Spark showed high growth rate, and JavaScript maintained the first position for programming languages.

Artificial Intelligence (AI) and related technologies have a long history of being used in education for motivating learners and enhancing learning. However, there have also been critiques for a too uncritical and naïve implementation of AI in education (AIED) and the potential misuse of the technology. With the release of the virtual assistant ChatGPT from OpenAI, many educators and stakeholders were both amazed and horrified by the potential consequences for education. One field with a potential high impact of ChatGPT is programming education in Computer Science (CS), where creating assessments has long been a challenging task due to the vast amount of programming solutions and support on the Internet. This now appears to have been made even more challenging with ChatGPT's ability to produce both complex and seemingly novel solutions to programming questions. With the support of data collected from interactions with ChatGPT during the spring semester of 2023, this position paper investigates the potential opportunities and threats of ChatGPT for programming education, guided by the question: What could the potential consequences of ChatGPT be for programming education? This paper applies a methodological approach inspired by analytic autoethnography to investigate, experiment, and understand a novel technology through personal experiences. Through this approach, the authors have documented their interactions with ChatGPT in field diaries during the spring semester of 2023. Topics for the questions have related to content and assessment in higher education programming courses. A total of 6 field diaries, with 82 interactions (1 interaction = 1 question + 1 answer) and additional reflection notes, have been collected and analysed with thematic analysis. The study finds that there are several opportunities and threats of ChatGPT for programming education. Some are to be expected, such as that the quality of the question and the details provided highly impact the quality of the answer. However, other findings were unexpected, such as that ChatGPT appears to be "lying" in some answers and to an extent passes the Turing test, although the intelligence of ChatGPT should be questioned. The conclusion of the study is that ChatGPT have potential for a significant impact on higher education programming courses, and probably on education in general. The technology seems to facilitate both cheating and enhanced learning. What will it be? Cheating or AI-enhanced learning? This will be decided by our actions now since the technology is already here and expanding fast. [Note: The publication year (2023) shown in the citation on the PDF is incorrect. The correct publication year is 2024.]

This paper reflects on the process of designing and implementing an update to the "Introduction to Information Technology" course at Bentley University, a business university in New England. Driven by a university-wide curriculum reform initiative and following best practices from digital literacy frameworks and IS model curricula, the new CS 100 course, entitled "Solving Business Problems with Information Technology," shifted emphasis from a personal computing context to exploring small business applications of technology. Students networked with university alumni at "Topics in Tech" presentations, where they learned about career options as information technology professionals. The authors describe the pilot courses that led to proposing a new CS 100 course and reflect its challenges and successes. Challenges included meeting the university's goal of transfer friendliness, scaling from a few pilots to multiple sections, consistency of course delivery, and evaluating assessment. Successes include placing course topics in a business context, introducing current technologies, and providing opportunities for students to learn about career opportunities and experiences from university alumni. The paper also describes how CS 100 aligns with the university's student learning goals for the new curriculum. These include developing future-focused skills, encouraging curiosity and critical analysis, communicating and collaborating in different settings, and demonstrating understanding of issues related to ethical use of technology.

Learning computer programming is typically difficult for newcomers. Demotivation and learned helplessness have received much attention. Besides the subject's intricacy, low in-class participation has been associated with poor student achievement. This paper presents a follow-up, stage 2 study on the novel instructional technique, Student-Driven Probe Instruction (SDPI), to address low in-class participation in programming courses. Instead of the teacher lecturing/explaining content to the class and asking questions, students were shown a snippet of code or other relevant material and given the option to ask questions beforehand. The study was conducted in two stages: stage 1 pilot and stage 2. This paper presents the results of stage 2, while stage 1 operations and results are discussed briefly. The number of questions asked in class, real-time Trello board postings, and emails/Slack conversations with the instructor were used to track participation. In-class participation showed significant improvement. Average quiz and in-class activity scores showed marginal gains. Results from the end-of-course survey show that students preferred SDPI over the traditional lecture style since it stirred their interest in the content and provided them the confidence to ask questions in class. The study is purely exploratory in nature, and no conclusions can be drawn due to the extremely small sample size of the student population.

Interest in the study of computer technology in schools (often in the form of Computer Science subjects or coding initiatives) is seen to have undergone two waves of interest, one in the late 1970s/early 1980s and the other more recently since about 2010. Through a historical exploration of the rationales for the study of computer technology in schools in both the first wave and the second wave, this paper aimed to explore the various curriculum ideologies underpinning their justification. In doing so, the paper highlights the chameleon-like nature of this change agenda in aligning with contemporary trends to advance the study of computer technology on the curriculum. The paper argues that current manifestations of the study of computer technology in schools are at odds with broader curriculum reform goals and international policies and raises questions about students' access to such knowledge.

This small scale study aims to analyze the question papers of Board of Intermediate and Secondary Education in the subject of computer science with reference to item analysis and Bloom's taxonomy. Data were collected from 100 students of Grade 9th and 10th from the schools of Lahore city using convenient sampling technique. Data collected on the papers developed by Board of Intermediate and Secondary Education for the year of 2015 and 2016. Item analyses were performed using Conquest software. Findings of the study shows that in the question papers conducted by Board of Intermediate and Secondary Education the majority questions were measuring the student abilities of knowledge and comprehension and only few questions were given to measure the student abilities to analyze, synthesize and evaluate, and this can be very helpful for the policy makers. Result of item analysis shows that many questions were not in the acceptable range of item difficulty and item discrimination. Items in the question papers were either too easy or too difficult. Findings revealed that the papers conducted and administered by Board of Intermediate and Secondary Education were not up to the mark, with reference to Bloom's taxonomy. The researcher recommended to train the assessment committee/panel developing the items. [ABSTRACT FROM AUTHOR]

Many universities have, or are facing, the task of providing high quality essential customer services with fewer financial and human resources. The growing diversity of students, their needs and proficiencies, along with the increasing variety of university program offerings, make providing customized, ondemand, automated solutions crucial to delivering high quality customer service. In this paper, the authors describe the development of an artificial intelligence-backed chatbot to aid in answering student advisement questions. The main objective of the chatbot is to provide 24/7 supplemental program specific advising assistance to graduate computer science majors to lessen the advising load of university faculty. In this paper, the authors describe the development of a chatbot prototype using IBM Watson Assistant running on a specially designed website and Slack platform to address frequently asked questions of computer science graduate students. Results of a pilot study conducted on 99 graduate students indicate that the prototype is a positive step forward in making student advising accessible, usable, and scalable to a broader audience.

This paper is an experiential report describing the faculty and student experiences and knowledge gained from developing an Internet of Things (IoT) course within an Information Technology (IT) Department at a large southeastern United States public university. The paper contributes insights gained developing the introductory IoT course, and it recommends the inclusion of IoT technology within an IT curriculum due to its disruptive and transformative nature. Many industries are deploying IoT applications making it imperative that IT graduates have the knowledge and skills needed to work with this emerging technology. The faculty leveraged the use of the ADDIE (Analyze, Design, Develop, Implement, and Evaluate) Instructional Design Model to develop a pilot course in the summer of 2022 and then, based on the pilot feedback and analysis using ADDIE, refined the course design for spring 2023. The continuing course development draws on IT undergraduate curricula guidelines in "Information Technology Curricula 2017 (IT2017)," research into how industry uses IoT applications, and the use of hands-on educational technologies to identify and apply IoT knowledge and skills needed for IT graduates. The pervasive nature of IoT requires IoT faculty to have knowledge of each of the IT Pillars (programming, networking, human-computer interaction, databases, and web systems) as well as the IT Supplemental IoT Domain guidelines developed in "IT2017."

The academic success of first-year students' learning in science faculties is by no means assured, especially in an Open Distance Learning setting with its limited number of face-to-face encounters between students and lecturers or tutors. Therefore, such encounters should be highly efficient in view of the considerable amount of knowledge transfer to students. The University of South Africa (Unisa) makes provision for contact sessions of 15 hours per semester for selected modules in an attempt to elevate the pedagogical efficiency of these sessions by focusing on the threshold concepts as an innovative way of learning. This paper shows that tutorials adopting the threshold concepts approach have the potential to make students academically more successful. The focus of this study is an introductory information systems module that teaches the Python programming language. Our statistical analysis demonstrated that the year marks and final exam scores of the participating students were frequently higher than those of the students in the control group.

This paper describes the study of enforcement of prerequisites in the Computer Science program at a regional university in the Southwest. Prerequisites are a significant factor in programs of study in higher education. Allowing students to register in courses may assume that they have existing knowledge and skills. Some programs treat prerequisites as advisory, while others consider them mandatory. In the latter case, procedures usually exist to make exceptions in the form of registration overrides. The state of prerequisite enforcement at our university over the years, and some factors that may have influenced adherence to the prerequisite structure over the years, will be discussed in this paper.

This paper proposes a Project-based team instruction methodology with open-ended projects to teach students critical analysis, design and implementation steps of developing Robotic Process Automation (RPA) for information systems. The use of project-based learning is appropriate for teaching RPA analysis and design with lean Six Sigma tools because of its experimental approach and documentation of logical steps needed to learn how to implement RPA successfully. The approach systematically documents work currently performed and defines future actions of the process while ensuring significant benefits are achieved with the RPA enhanced process. This methodology is important because the application of RPA is not commonly taught in Management Information System (MIS) programs. MIS students may not understand the significance of combined methodology, RPA tool, and usefulness of RPA until they enter the workforce where RPA is rapidly becoming available and easier to implement. The lecture sessions and exercises are valuable because it is easy to communicate the value of RPA in terms of time, quality, volume of transactions, etc. using Lean Six Sigma analytic approaches. The exercises involve hands on activities to make this learning experience interesting for students to readily associate the theoretical process improvement agreement and visualize the practical value of RPA enhanced projects. The paper discusses the need for process changes (and new development approaches) in organization to match the properties and functions within enterprise systems and ERPs that has led to criticism of the enterprise systems. This criticism is attributable to the ERPs' many subfunctions and operations that have limited adaptability and reduced functional and operational flexibility. The RPAs require limited prior knowledge of ERPs or their sub-processes for the improvements that are made in the performance of the organization. Thus, students do not have to "learn" how these enterprise or ERP systems operate to make changes or task improvements. This paper presents a project-based methodology and design approach focusing on development of RPAs that help students learning how to make the improvements using the RPS tools. The students learn that projects can deliver significant and tangible benefits to organizations while engaging students in key activities of the analysis, design and development process from a low code-no code perspective.

This paper unites the history of Computer Science (CS) Education in Ireland by plotting Ireland's roadmap leading to the implementation of formal Computer Science Education in schools. It first outlines the educational system in Ireland. The history roadmap starts in the 1970s with the first notions of introducing computing in post-primary school, and then continues up to the roll-out the CS curriculum in Ireland at the Senior Cycle level in 2018. The story is chiefly available in disparate publications and reports, so piecing together the entire story is often difficult. This paper collates the available literature, together with the authors' local knowledge of the process, into one paper that may be of interest locally and of value to other jurisdictions beginning their planning of national curricula. The paper describes the development and the current situation of the formal curricula in CS at second level. The current landscape of Computing Education at primary level, which at the time of writing is in the planning stages in Ireland, is described. Additionally, an investigation into the introduction of Computing Education in schools in the international jurisdictions that directly influenced the Irish roll-out takes place, to summarize any lessons learned that might provide insights for Ireland going forward.

In programming problem solving activities, sometimes, students need feedback to progress in the course, being positively affected by the received feedback. This paper presents an overview of the state of the art and practice of the feedback approaches on introductory programming. To this end, we have carried out a systematic literature mapping to understand and discuss the main approaches for providing and evaluating feedback used in the learning of novice programmers in the problem-solving activity. Thus, according to a formal protocol, an automatic search was performed for papers from 2016 to 2021. As a result, 39 studies were selected for the final analysis. As a result, we propose three different categorizations: the main approaches to providing feedback, the main methods used in the evaluation and the main aspects and effects of the evaluated feedback.

The global spread of the COVID-19 pandemic posed unprecedented challenges to higher education institutions worldwide. As governments announced lockdown measures that placed restrictions and mandatory closures on establishments that traditionally required gatherings, universities worldwide cancelled face-to-face classes and adapted their mode of offering to online teaching and learning. Using an interpretive study based on a single case, this paper presents the author's most profound experiences with online teaching and learning of the Data Structures and Algorithms course at the University of Namibia (UNAM). Throughout the teaching of this course, the author kept an up-to-date reflective practice journal, and required her students to engage in reflective practice. The author also had an opportunity to engage and discuss her experiences with other lecturers in the School of Computing. The paper therefore presents a narrative of reflections on the meaning of teaching and learning as adapted to emergency online teaching during the COVID-19 pandemic. Findings suggest that reflective practice during emergency online teaching presents an opportunity for educators to experiment with new delivery approaches, as well as to monitor how their interventions can impact the achievement of learning outcomes.

One only needs to listen to the news reports to recognize that the gap between securing the enterprise and cybersecurity threats, breaches, and vulnerabilities appears to be widening at an alarming rate. An untapped resource to combat these attacks lies in the students of the secondary educational system. Necessary in the cybersecurity education is a 3-tiered approach to quickly escalate the student into a workplace-ready graduate. The analogy used is a three-legged-stool, where curriculum content, hands-on skills, and certifications are equal instruments in the edification of the cybersecurity student. This paper endeavors to delve into the 3rd leg of the stool by developing the concept of vendor-specific and vendor-neutral certifications to educate the cybersecurity student and test their capability of protecting the workplace. The research data was drawn from companies in the Atlanta, Georgia area, who employ and hire cybersecurity recruits. The data from the research proves certifications are necessary as an addition to the cybersecurity curriculum in the secondary education arena. The paper reviews the need for cybersecurity graduates, the balance between cybersecurity theory and applied skillsets, the difference between a certificate and a certification, benefits to the community, classifications of certifications, relevancy of a college degree in today's workforce, and recommendations for further study.

The goal of this paper is to bring new insights to the study of social learning processes by designing measures of collaboration using high-frequency sensor data. More specifically, we are interested in understanding the interplay between moments of collaboration and cooperation, which is an understudied area of research. We collected a multimodal dataset during a collaborative learning activity typical of makerspaces: learning how to program a robot. Pairs of participants were introduced to computational thinking concepts using a block-based environment. Mobile eye-trackers, physiological wristbands, and motion sensors captured their behavior and social interactions. In this paper, we analyze the eye-tracking data to capture participants' tendency to synchronize their visual attention. This paper provides three contributions: (1) we use an emerging methodology (mobile dual eye-tracking) to capture joint visual attention in a co-located setting and replicate findings that show how levels of joint visual attention are positively correlated with collaboration quality; (2) we qualitatively analyzed the co-occurrence of verbal activity and joint visual attention in low and high performing groups to better understand moments of collaboration and cooperation; (3) inspired by the qualitative observations and theories of collaborative learning, we designed a new quantitative measure that captures cycles of collaborative and cooperative work. Compared to simple measures of joint visual attention, we found it to increase correlation coefficients with learning and collaboration scores. We discuss those results and describe how advances in analyzing sensor data can contribute to theories of collaboration. We conclude with implications for capturing students' interactions in co-located spaces using Multimodal Learning Analytics (MMLA).

Lately, there has been a rising trend towards integrating sustainability issues and implementing sustainable development (SD) goals into higher education, especially in the Information and Communication Technology (ICT) field. This paper presents the challenges of the introduction of education for sustainability in higher education institutions, analyzes how these challenges could be addressed, and records the essential principles that can guide the incorporation of SD education in higher education. At the same time, this paper advocates the concept of sustainability integration into undergraduate ICT curricula and provides indications for developing ICT curricula that integrate sustainability issues. This paper also examines the contribution of education to the environmental awareness of the students at a Greek University while it captures their perceptions regarding the necessity for the inclusion of sustainability in the ICT curricula. The results are based on the processing of two questionnaires (pre-test and post-test data) distributed during two lectures regarding sustainability at a two-week interval. The findings of the study prove that the direct effect of the educational intervention on the intention of the students to engage in sustainability is significant. Furthermore, it is observed that students show a positive attitude towards integrating sustainability issues into their ICT education. In addition, although students had a deficient level of understanding of the concept of SD goals before the intervention, they showed a significant increment in their previous knowledge regarding sustainability and the environmental impact of ICT studies. The research also reveals that the students are not satisfied with the engagement of the university towards sustainability, and they propose various awareness activities to support their engagement with sustainability issues in an inclusive manner.

We conducted a systematic literature review on automated grading and feedback tools for programming education. We analysed 121 research papers from 2017 to 2021 inclusive and categorised them based on skills assessed, approach, language paradigm, degree of automation, and evaluation techniques. Most papers assess the correctness of assignments in object-oriented languages. Typically, these tools use a dynamic technique, primarily unit testing, to provide grades and feedback to the students or static analysis techniques to compare a submission with a reference solution or with a set of correct student submissions. However, these techniques' feedback is often limited to whether the unit tests have passed or failed, the expected and actual output, or how they differ from the reference solution. Furthermore, few tools assess the maintainability, readability, or documentation of the source code, with most using static analysis techniques, such as code quality metrics, in conjunction with grading correctness. Additionally, we found that most tools offered fully automated assessment to allow for near-instantaneous feedback and multiple resubmissions, which can increase student satisfaction and provide them with more opportunities to succeed. In terms of techniques used to evaluate the tools' performance, most papers primarily use student surveys or compare the automatic assessment tools to grades or feedback provided by human graders. However, because the evaluation dataset is frequently unavailable, it is more difficult to reproduce results and compare tools to a collection of common assignments.

The computing education research community now has at least 40 years of published research on teaching ethics in higher education. To examine the state of our field, we present a systematic literature review of papers in the "Association for Computing Machinery" computing education venues that describe teaching ethics in higher-education computing courses. Our review spans all papers published to SIGCSE, ICER, ITiCSE, CompEd, Koli Calling, and TOCE venues through 2022, with 100 papers fulfilling our inclusion criteria. Overall, we found a wide variety in content, teaching strategies, challenges, and recommendations. The majority of the papers did not articulate a conception of "ethics," and those that did used many different conceptions, from broadly applicable ethical theories to social impact to specific computing application areas (e.g., data privacy and hacking). Instructors used many different pedagogical strategies (e.g., discussions, lectures, assignments) and formats (e.g., stand-alone courses, incorporated within a technical course). Many papers identified measuring student knowledge as a particular challenge, and 59% of papers included mention of assessments or grading. Of the 69% of papers that evaluated their ethics instruction, most used student self-report surveys, course evaluations, and instructor reflections. While many papers included calls for more ethics content in computing, specific recommendations were rarely broadly applicable, preventing a synthesis of guidelines. To continue building on the last 40 years of research and move toward a set of best practices for teaching ethics in computing, our community should delineate our varied conceptions of ethics, examine which teaching strategies are best suited for each, and explore how to measure student learning.

The HCS12 microcontroller and DRAGON12-Light Trainer boards are extensively utilized in microprocessor system design education. This paper details the rationale, approach, and outcomes from implementing the DRAGON12-Light Trainer board in teaching an upper-level undergraduate microprocessors course at Oakland University. The course's primary goal is for students to acquire the skills necessary to design both hardware and software for microprocessor-based systems, with applications across various industries. The paper assesses the effectiveness of employing the Motorola HCS12 microcontroller for its real-world relevance and integrates the Freescale CodeWarrior IDE v5.1 environment for software development. This research uniquely contributes by measuring the improvement in students' practical skills, specifically in hardware and software design using assembly and C programming, through hands-on lab assignments. It reports on the development of students' abilities to engage in microprocessor-based system design and critically evaluates the applied aspects of pedagogy by incorporating the DRAGON12-Light Trainer in lab exercises, such as those involving 'Measuring Human Reaction Time' and 'Servo motor interfacing.' Quantitative results, derived from student surveys and assessments, indicate significant improvements in students' programming competencies. The paper provides statistical results showcasing the increase in students' self-rated confidence levels in assembly and C language programming before and after course completion. Additionally, qualitative insights are discussed, reflecting students' experiences and the perceived applicability of the skills they acquired. These results underscore the pedagogical value of integrating practical training devices like the DRAGON12-Light Trainer board into microprocessors curricula.

This paper presents field-tested improvements over an 11-year period of a large-scale "Introduction to Information Systems" core business school course and provides a framework for implementation. Engagement and learning in large-scale courses can prove challenging, especially when the class is a requirement within a business school's core curriculum where most students taking the class are not majors in the course's subject matter. The course sections typically have 100 or more students each. The non-IS major student population attends this core course because they must, rather than want to, attend which in most cases leads to indifference and disengagement. A primary need and challenge of a required core course are to create a compelling 14-week "Introduction to Information Systems" course that captures this student population's interest in an engaging manner. This paper identifies an innovative approach to create and foster an enhanced learning environment organized around active learning, dynamic content, and a narrative structure. Major changes discussed in the paper are the abandonment of textbooks, the introduction of in-class activities and JavaScript coding, and the establishment of a narrative.

Objective: Community college transfer pathways are critical for advancing gender equity in STEM. Yet, community college students are often ignored within studies of women's participation in undergraduate computing. In a first effort to address this gap in the literature, this paper explores the composition of transfer-intending computing students over time (Study One) and gender differences in the characteristics and experiences of transfer-intending computing students (Study Two). Methods: This descriptive paper uses Center for Community College Student Engagement (CCCSE) survey data. Study One relies on a sample of nearly 30,000 transfer aspirants in computing across the United States between 2011 and 2019, allowing us to explore trends over time. Study Two examines a subset of over 9,000 students from the most recent survey cohort, providing a more nuanced snapshot of transfer-intending computing students. Descriptive statistics were used to examine how student experiences differ by gender and race/ethnicity. Results: Study One findings show that women's representation among transfer-intending computing students has declined over time. Study Two results reveal that, relative to men, women spend more time caregiving, commuting, studying, in student groups, and utilizing advising services, pointing to unique demands on women's time. We also identify significant differences in how Black and Indigenous women financed their college, relative to other women. Conclusions: While women are underrepresented among transfer-intending computing students, they represent a diverse group to support. We point to recommendations for policy and practice to support transfer-intending women in STEM and future research that considers intersectional identities among this diverse group.

Purpose: In today's digital world, data-driven digital artefacts pose challenges for education, as many students lack an understanding of data and feel powerless when interacting with them. This paper aims to address these challenges and introduces the data awareness framework. It focuses on understanding data-driven technologies and reflecting on the role of data in everyday life. The paper also presents an empirical study on young school students' data awareness. Design/methodology/approach: The study involves a teaching unit on data awareness framed by a pre- and post-test design using a questionnaire on students' awareness and understanding of and reflection on data practices of data-driven digital artefacts. Findings: The study's findings indicate that the data awareness framework supports students in understanding data practices of data-driven digital artefacts. The findings also suggest that the framework encourages students to reflect on these data practices and think about their daily behaviour. Originality/value: Students learn a model about interactions with data-driven digital artefacts and use it to analyse data-driven applications. This approach appears to enable students to understand these artefacts from everyday life and reflect on these interactions. The work contributes to research on data and artificial intelligence literacies and suggests a way to support students in developing self-determination and agency during interactions with data-driven digital artefacts.

As universities shifted to online education with the onset of the Coronavirus Disease 2019 (COVID-19) pandemic, both pedagogy and assessment patterns across disciplines underwent a change, with a shift towards collaborative digital assessments. In this context, using qualitative and quantitative methods for data collection from an assessment conducted for 55 students who worked in groups to create YouTube videos on pre-selected modules, our analysis reveals that this assessment tool had a significant impact on peer learning, motivation and group dynamics. Students were more motivated to learn and share their learning, and they could also successfully engage in recognising and addressing group dynamics, thereby cultivating more than just subject knowledge. This finding aligns with existing scholarship and the paper adds to research about pedagogy and assessment via digital education in the Indian context, which is still upcoming.

There can be many reasons why students fail to answer correctly to summative tests in advanced computer science courses: often the cause is a lack of prerequisites or misconceptions about topics presented in previous courses. One of the ITiCSE 2020 working groups investigated the possibility of designing assessments suitable for differentiating between fragilities in prerequisites (in particular, knowledge and skills related to introductory programming courses) and advanced topics. This paper reports on an empirical evaluation of an instrument focusing on data structures, among those proposed by the ITiCSE working group. The evaluation aimed at understanding what fragile knowledge and skills the instrument is actually able to detect and to what extent it is able to differentiate them. Our results support that the instrument is able to distinguish between some specific fragilities (e.g., value vs. reference semantics), but not all of those claimed in the original report. In addition, our findings highlight the role of relevant skills at a level between prerequisite and advanced skills, such as program comprehension and reasoning about constraints. We also suggest ways to improve the questions in the instrument, both by improving the distractors of the multiple-choice questions, and by slightly changing the content or phrasing of the questions. We argue that these improvements will increase the effectiveness of the instrument in assessing prerequisites as a whole, but also to pinpoint specific fragilities.

This paper presents the first experiences of the use of an online open-source repository with programming exercises. The repository is independent of any specific teaching approach. Students can search for and select an exercise that trains the programming concepts that they want to train and that only uses the programming concepts they already know, then submit their solutions, and get automatic feedback from the system. We analyzed quantitatively how students used the system by inspecting the logged actions of the students using the system. We also did a qualitative analysis by interviews, to find out how the students appreciated the use of the repository and to get feedback for improvements. We focused on how students select exercises as finding the exercise that fulfils the training needs of a student is the innovative part of our repository.

Teaching programming is a complex process requiring learning to develop different skills. To minimize the challenges faced in the classroom, instructors have been adopting active methodologies in teaching computer programming. This article presents a Systematic Mapping Study (SMS) to identify and categorize the types of methodologies that instructors have adopted for teaching programming. We evaluated 3,850 papers published from 2000 to 2022. The results provide an overview and comprehensive view of active learning methodologies employed in teaching programming, technologies, programming languages, and the metrics used to observe student learning in this context. In the results, we identified thirty-seven different ALMs adopted by instructors. We realized that seventeen publications describe teaching approaches that combine more than one ALM, and the most reported methodologies in the studies are Flipped Classroom and Gamification-Based Learning. In addition, we are proposing an educational and collaborative tool called CollabProg, which summarizes the primary active learning methodologies identified in this SMS. CollabProg will assist instructors in selecting appropriate ALMs that align with their pedagogical requirements and teaching programming context.

When it comes to mastering the digital world, the education system is more and more facing the task of making students competent and self-determined agents when interacting with digital artefacts. This task often falls to computing education. In the traditional fields of computing education, a plethora of models, guidelines, and principles exist, which help scholars and teachers identify what the relevant aspects are and which of them one should cover in the classroom. When it comes to explaining the world of digital artefacts, however, there is hardly any such guiding model. The ARIadne model introduced in this paper provides a means of explanation and exploration of digital artefacts which help teachers and students to do a subject analysis of digital artefacts by scrutinizing them from several perspectives. Instead of artificially separating aspects which target the same phenomena within different areas of education (like computing, ICT or media education), the model integrates technological aspects of digital artefacts and the relevant societal discourses of their usage, their impacts and the reasons behind their development into a coherent explanation model.

The United States faces persistent threats conducting malicious cyber campaigns that threaten critical infrastructure, companies and their intellectual property, and the privacy of its citizens. Additionally, there are millions of unfilled cybersecurity positions, and the cybersecurity skills gap continues to widen. Most companies believe that this problem has not improved and nearly 44% believe it has gotten worse over the past 10 years. Threat actors are continuing to evolve their tactics, techniques, and procedures for conducting attacks on public and private targets. Education institutions and companies must adopt emerging technologies to develop security professionals and to increase cybersecurity awareness holistically. Leveraging Virtual/Augmented/Mixed/Extended Reality technologies for education, training, and awareness can augment traditional learning methodologies and improve the nation's cybersecurity posture. This paper reviews previous research to identify how distance and remote education are conducted generally, and how Virtual/Augmented/Extended/Mixed reality technologies are used to conduct cybersecurity awareness training, cybersecurity training, and conduct operations. Finally, barriers to adopting these technologies will be discussed. Understanding how these technologies can be developed and implemented provides one potential way of overcoming the cybersecurity workforce gap and increasing the competencies and capabilities of cybersecurity professionals.

Service-Learning (SL) is a powerful methodology to acquire competences and values in Higher Education. However, there is still no widespread use in Information and Computer Science (ICS) degrees where most of the subjects are focused on the development of theoretical and practical contents purely related to technical competences. In this paper, we show the structure of a SL methodology to develop Bachelor's Thesis: 1) definition of proposals considering all the competencies of the Bachelor's Thesis subject and the needs of entities; 2) development of applications using agile methodologies, and 3) assessment of the SL experience from students, entities and professors. We present an experience developed in the 2019/2020 academic year with two entities devoted to disfavoured people. The results show both the high technical and professional quality of the projects and the high satisfaction of entities and students. We hope that the development of applications with the collaboration of non-profit entities allows the acquisition of both specific and transversal competencies on ICS degrees at the same time enhancing the development of useful professional ones.

This study was conducted to determine the effects of blog-based teaching on academic achievement and pre-service teachers' ideas about this implementation. Participants of the study consist of 51 sophomore students of the department of Computer Education and Educational Technology in Inonu University, Turkey. The research method is a mixed method in which qualitative and quantitative methods are combined. Pretest and post-test quasi-experimental method with control group in the quantitative part and case study in the qualitative part were used. Experimental procedure lasted for 5 weeks during 'Assessment and Evaluation' course that is among the teacher education programs. The web blog was prepared by the researchers in accordance with the purpose of this study, the data was collected through an academic achievement test and interview form. At the end of the research, there is a significant difference between the pre-tests and post-tests of the experimental and control groups. No significant difference between the post-tests of the groups and retention was found. It was observed from the interviews that besides the advantages such as facilitating preparation for the lesson, information sharing, active participation and increase in achievement, there were disadvantages of blog-based teaching such as achieving not a full form of participation, internet and computer requirements. Also, it was concluded that blog-based teaching can be used mostly in verbal lessons by rich resources and data diversification. [This paper was presented at The 3rd International Congress on Curriculum and Instruction, October 22-24, 2015, Adana, Turkey.]

This paper focuses on the undergraduate experiences in computer sciences (CS) disciplines of eight Native women and two-spirit undergraduates and how their values and experiences around the communal goal of giving back enable them to persist in computing. The paper draws from a one-year study that included participants across the U.S.A from predominantly White institutions, Native serving institutions, and tribal colleges. Utilizing the decolonizing and participant-centered methods of photo elicitation, our interviews used photographs taken by participants as starting points for conversations. This method resulted in deep understandings of participants' experiences of the supports and barriers in their CS programs, and of the importance of giving back for persistence. We adapt Page-Reeves and colleagues' 2019 framework for giving back and Native students in STEM--particularly the concepts of giving back as a Native value and giving back in the context of CS education--to illuminate the ways in which participants persisted and navigated their identities as Native students and emergent computer scientists. We also introduce a new concept, culturally connected giving back, to describe the ways in which Native undergraduates in computing contributed, or planned to contribute, towards technology sovereignty and cultural preservation. CS, like many STEM fields, is typically viewed as highly individualistic and not aligned with communal goals of helping others. However, Native participants in this study identified computing as having the potential for giving back. They incorporated a broad range of giving back actions into their computing professional identities through teaching, mentoring, serving as role models, creating counterspaces, or preserving their cultures using their computing skills. Through giving back, participants fulfilled a sense of obligation to their communities or counteracted negative stereotypes about Native learners. Beneficiaries of these acts of giving back included Native and other minoritized peers, younger students, home communities, and other Native communities. Importantly, opportunities to give back served as strong motivators to persist in CS in spite of challenges. We discuss the implications of these findings for policy and practice and also explore the implications for how institutions and CS departments can support Native student recruitment, retention, and success.

Computer programming is a skill of increasing importance in scientific and technological fields. However, in introductory computer science (CS1) courses in higher education, approximately one in every three students fails. A common reason is that students are overwhelmed by an accelerated and inflexible pace of learning that jeopardizes success. Accordingly, in the computer science education literature it has been suggested that the pedagogical philosophy of 'mastery learning,' which supports students progressing at their own pace, can improve academic outcomes of CS1 courses. Nevertheless, few extended mastery learning implementations in CS1 have been documented in the literature, and there is a lack of guidance and best practices to foster its adoption. In this paper, we present a four-year action research study in which a modular mastery-based CS1 course was designed, evaluated and improved in successive iterations with cohorts of engineering freshmen in a Latin American research university (N = 959). In the first year of the intervention, only 19.3% of students passed the course in their first semester attempting it. In successive iterations, the instructional design, teaching and learning activities, course content, and course management were iteratively improved such that by the fourth year of offering 77.1% of students passed the course in their first semester. Over this period, course attrition was reduced from 25.0% to 3.8% of the cohort, and students' mean time spent in the course decreased from 23.2 weeks (SD = 7.38) to 14.9 (SD = 3.64). Results indicate that modularization for mastery learning is a viable approach for improving academic results in a CS1 course. Practical considerations towards successful implementation of this approach are presented and discussed.

Primary school children frequently use digital devices, which can be infected by computer viruses. In this mixed methods paper with two studies (N = 278 + 114), we examined 8-year-olds' preconceptions about computer viruses and protection against them; how to teach these children about said topics using three different, 30-min-long, content-equivalent lessons; and what knowledge the children can acquire. We found that participants had limited prior knowledge of computer viruses and almost no knowledge about protection against them. However, they rarely had misconceptions. They learnt, and retained over a month, key general points and a few specific points about this domain. Acquired knowledge was still somewhat patchy, most likely represented in 'pieces' rather than as complex, theory-like chunks. Nevertheless, all three approaches produced notable learning gains (d > 1.78). A lesson organized around a narrative 5-min video and six < 1 min video snippets was the most effective: compared to a lesson organized around two 5-min videos (d = 0.89) and a teacher-led lesson without videos (d = 0.54). The findings are consistent with contemporary instructional design theories and 'knowledge in pieces' conceptual change frameworks. They imply that the topic of computer viruses should be included in second-graders' curricula.

Computer science is often integrated within early childhood education (ECE) through the use of educational robots. This requires adequate preparation of ECE teachers to program and debug, which can be done with scaffolding. In this paper, we use a QUANT + qual mixed method approach incorporating lag sequential analysis, ICAP framework coding, sentiment analysis, and supplementary qualitative analysis. Students tended to engage more with tasks in the revision and evaluation phases than in the exploration phase, and became less dependent on scaffolding prompts and more competent in debugging, as debugging task complexity increased. This study addresses a key gap in the scaffolding literature in that it examined learners' interactions with scaffolding for evidence of decreased reliance on scaffolding.

Children's preschool years are crucial for the development of computational thinking (CT) skills. However, debate continues regarding whether CT should be developed through plugged-in or unplugged activities. This study investigated the similarities and differences between plugged-in and unplugged activities with similar learning content and assessment methods for cultivating computational thinking (CT) in young children. Twenty-four young children (aged 5-6 years) from a kindergarten in Foshan, China, were randomly assigned to either the plugged-in or unplugged group to participate in a five-week study. In the plugged-in group, Dodobot was used in the classroom, while in the unplugged group, unplugged materials such as paper, pencil and tangram puzzles were used. Research results indicate that 1) both plugged-in and unplugged activities significantly improved the young children's CT skills after a short-term educational intervention, but there were no significant differences between the two groups; 2) the extent to which the plugged-in and unplugged activities promoted subdimensions of CT was different, with the plugged-in group demonstrating significant improvements in hardware, algorithm, and modularity and the unplugged group demonstrating significant improvements in terms of representation; 3) the children from both the plugged-in and unplugged groups showed high motivation; And 4) the children in both the plugged-in and unplugged groups showed cooperative behaviors. The frequency of cooperative behavior was more related to materials, and cooperation quality was more related to teacher guidance.

This research was triggered by the identified need in literature for large-scale studies about the kinds of designs that teachers create for mobile learning (m-learning). These studies require analyses of large datasets of learning designs. The common approach followed by researchers when analyzing designs has been to manually classify them following high-level pedagogically guided coding strategies, which demands extensive work. Therefore, the first goal of this paper is to explore the use of supervised machine learning (SML) to automatically classify the textual content of m-learning designs using pedagogically relevant classifications, such as the cognitive level demanded by students to carry out specific designed tasks, the phases of inquiry learning represented in the designs, or the role that the situated environment has in the designs. Because not all SML models are transparent, but researchers often need to understand their behaviour, the second goal of this paper is to consider the trade-off between models' performance and interpretability in the context of design analytics for m-learning. To achieve these goals, we compiled a dataset of designs deployed using two tools, Avastusrada and Smartzoos. With this dataset, we trained and compared different models and feature extraction techniques. We further optimized and compared the best performing and most interpretable algorithms (EstBERT and Logistic Regression) to consider the second goal with an illustrative case. We found that SML can reliably classify designs with accuracy > 0.86 and Cohen's kappa > 0.69.

Object-oriented programming distinguishes between instance attributes and methods and class attributes and methods, annotated by the "static" modifier. Novices encounter difficulty understanding the means and implications of "static" attributes and methods. The paper has two outcomes: (a) a detailed classification of aspects of understanding "static," and (b) a collection of questions designed to serve as a learning/practice/diagnostic tool to address those aspects. Providing answers requires learners to apply higher-order cognitive skills and, hence, to advance their understanding of the essential meaning of the concept. Each question is analyzed according to three characteristics: (a) the "static" aspects that the question examines according to a detailed classification the paper provides; (b) identification of the question according: to Bloom's revised taxonomy, to the Structure of Observed Learning Outcome (SOLO) taxonomy; and to the problem-solving keywords used in the question's formulation. Several recommendations for teaching are presented.

Vocabulary knowledge is very crucial for learners who want to be competent in a language. Vocabulary knowledge means having the knowledge of or command over words of a language and their usages in real-life contexts. Vocabulary knowledge can be gained incidentally and intentionally. The paper compares the effectiveness of the reading-only condition and reading-while-listening condition in incidental vocabulary acquisition. It seeks to find out whether students acquire more vocabulary knowledge by reading a text only or reading the text while listening to it. It also disseminates the effect of word exposure frequency. By applying four vocabulary tests, it proves that learners can gain vocabulary knowledge in both the conditions; but the reading-while-listening condition can result in more gain of vocabulary knowledge. The paper also shows that the more the number of encounters with words in context, the more the vocabulary gains. Studies with students from different levels of education and gender based studies can be conducted. This is a pioneering study on this topic in Bangladesh, so the paper will pave a way for the researchers who want to work on the same topic.

The underrepresentation of certain groups in computing has led to increasing efforts to develop computing curricula that is responsive and relevant to a more diverse group of learners. The current paper used a Quick Scoping Review methodology to identify research that has implemented and evaluated culturally responsive and relevant K-12 computing curricula, and to understand how they have been designed, the methods used for evaluation, and the factors affecting their success. In total, 12 papers were included in the review, and all were from a United States setting. Successes included changing learners' attitudes towards computing and increased learning gains. Key factors in the implementation of the curricula were teacher confidence and understanding of the socio-political context of computing, opportunities provided for collaboration and sharing knowledge and opinions, and allowing time for difficult discussions without oversimplifying the issues. The review identifies important lessons to be learned for educators around the world who are aiming to increase diversity in representation in computing in their schools.

This paper describes changes, precipitated by the COVID-19 pandemic, to a capstone MIS class using Microsoft ASP.NET MVC for team development with live-clients. The advent of the pandemic required that the entire development effort of the class immediately transition from a largely in-class development effort with local SQL Server and Web Server Instances to one requiring all development be done in a virtual desktop interface (VDI). The VDI was the only way for students to get to both the SQL Server instance and the web server where they published their applications. Code availability, version control and joint development issues were resolved with Git and the Visual Studio interface to GitHub. This paper summarizes the development issues faced by the student teams, how they were resolved and provides a brief introduction to the use of GitHub from within the current version of Visual Studio. The paper is descriptive, and the subjective nature of the live-client project deliverables made any significant statistical analysis impossible.

Algorithmic Thinking (AT) skills may be considered one of the necessary skills for everyone in the new century. Individuals and societies live in a time when they cannot avoid using information communication technologies (ICT). Hence, they need to be ICT literate. Teachers shall play an important role both for individuals and societies to address this need. However, are they ready to play such a role? This paper presents a suggestion for teacher training to help teachers how to play the role. The paper suggests including an elective course under the title AT into the computer science teacher training curricula and aims to present the course, progress and views of the students who took the course. A mixed-method approach was followed for the current study. The study was carried out with the participation of sixth-semester students of a Computer Education and Instructional Technology Department of an Education Faculty who may be considered prospective computer science teachers. Twenty-eight students were enrolled in the elective AT course offered for the period. Within the scope of the study, development of the course curriculum, instructional process of the course and evaluation of the course, in line with students' views and exam scores, are presented. Findings of the research suggest that the students find the Algorithmic Thinking course helpful for them to acquire some algorithmic thinking skills as well as some other academic and life-related thinking abilities. Also, the course may be considered as a necessary course particularly for the training process of computer science teachers. In addition, the students think that the offered course was effective and beneficial.

The skills and competencies of IT professionals are often described using employer-led skills frameworks. They express competencies as technical knowledge and skills combined with a range of personal qualities. Employers have indicated the importance of developing such qualities for new graduates. In response, recent ACM/IEEE curricular recommendations have shifted their emphases from bodies of knowledge to the development of competencies. The IT2017 ACM/IEEE Curriculum Guidelines for Baccalaureate Degree Programs proposed a model of IT competency comprising three interrelated components: content knowledge, skills, and dispositions, where dispositions represent personal qualities desirable in the workplace. The ACM/IEEE Computing Curricula 2020 (CC2020) report enriched the IT2017 disposition concept by identifying eleven dispositions that all computing programs should include for the career preparation of their graduates. However, developing and assessing dispositions in a degree program remain challenges, often involving internships, work placements and similar student opportunities. A recent mapping of the eleven CC2020 dispositions to the responsibility characteristics of the Skills Framework for the Information Age (SFIA), a widely used professional skills framework, suggested a promising approach to addressing this challenge. Inspired by this mapping, this paper aims to help educators assess students' achievement of CC2020 dispositions by mapping real-world experiences they have recorded in individual portfolios against the SFIA responsibility characteristics. First, the selection of SFIA to operationalize the CC2020 dispositions is validated by demonstrating that alternative frameworks pose significant challenges for any assessment approach that needs to be independent of particular technical skills. A tool is described that maps demonstration of SFIA responsibility characteristics to CC2020 dispositions, applying a simple, consistent assessment algorithm. Finally, the assessment process and outcomes are illustrated using a fictional student portfolio, constructed to reflect one author's experience of work placement students' achievements.

Recent years have witnessed a growing demand for business analytics-oriented curricula. This paper presents the implementation of an introductory Python course at a business university and the attempt to elevate the course's relevance by introducing data analytics topics. The results from a survey of 64 undergraduate students of the course are analyzed to understand their perceived relevance of having Python programming skills upon entering the workplace, and how course design and other student characteristics influenced the perceptions of their learning and performance. Results demonstrate that business students are highly motivated to take Python programming courses to better position themselves for future career opportunities in the growing field of data analytics. We also found that students with no prior programming experience performed better than students who had some prior programming experience, suggesting that Python is an appropriate choice for a first programming language in the Information Systems (IS) curriculum. The paper concludes with recommendations for offering an analytics-focused first programming course to bring added relevance to IS students learning programming skills.

Use of theory within a field of research provides the foundation for designing effective research programs and establishing a deeper understanding of the results obtained. This, together with the emergence of domain-specific theory, is often taken as an indicator of the maturity of any research area. This article explores the development and subsequent usage of domain-specific theories and theoretical constructs (TCs) in computing education research (CER). All TCs found in 878 papers published in three major CER publication venues over the period 2005-2020 were identified and assessed to determine the nature and purpose of the constructs found. We focused more closely on areas related to learning, studying, and progression, where our analysis found 80 new TCs that had been developed, based on multiple epistemological perspectives. Several existing frameworks were used to categorize the areas of CER focus in which TCs were found, the methodology by which they were developed, and the nature and purpose of the TCs. A citation analysis was undertaken, with 1,727 citing papers accessed to determine to what extent and in what ways TCs had been used and developed to inform subsequent work, also considering whether these aspects vary according to different focus areas within computing education. We noted which TCs were used most often and least often, and we present several brief case studies that demonstrate progressive development of domain-specific theory. The exploration provides insights into trends in theory development and suggests areas in which further work might be called for. Our findings indicate a general interest in the development of TCs during the period studied, and we show examples of how different approaches to theory development have been used. We present a framework suggesting how strategies for developing new TCs in CER might be structured and discuss the nature of theory development in relation to the field of CER.

The use of established and discipline-specific theories within research and practice is an indication of the maturity of a discipline. With computing education research as a relatively young discipline, there has been recent interest in investigating theories that may prove foundational to work in this area, with discipline-specific theories and many theories from other disciplines emerging as relevant. A challenge for the researcher is to identify and select the theories that provide the best foundation for their work. Learning is a complex and multi-faceted process and, as such, a plethora of theories are potentially applicable to a research problem. Knowing the possible candidate theories and understanding their relationships and potential applicability, both individually or as a community of theories, is important to provide a comprehensive grounding for researchers and practitioners alike. In this work, we investigate the fundamental connections between learning theories foundational to research and practice in computing education. We build a comprehensive list of 84 learning theories and their source and influential papers, which are the papers that introduce or propagate specific theories within the research community. Using Scopus, ACM Digital Library, and Google Scholar, we identify the papers that cite these learning theories. We subsequently consider all possible pairs of these theories and build the set of papers that cite each pair. On this weighted graph of learning theory connections, we perform a community analysis to identify groups of closely linked learning theories. We find that most of the computing education learning theories are closely linked with a number of broader learning theories, forming a separate cluster of 17 learning theories. We build a taxonomy of theory relationships to identify the depth of connections between learning theories. Of the 294 analysed links, we find deep connections in 32 links. This indicates that while the computing education research community is aware of a large number of learning theories, there is still a need to better understand how learning theories are connected and how they can be used together to benefit computing education research and practice.

The Autonomous Vehicles (AV) are a self-driving vehicle capable of sensing its environment and operating with minimal or no human intervention converting into a fully or partially automated vehicle. These automated vehicles have great potential to revolutionize the automotive industry and our daily lives. Thus, they are receiving a lot of attention from automotive industries, governments, suppliers, educational sectors, researchers, and many other stakeholders. According to global financial service firm UBS, the AV market could reach more than $2 trillion by 2030. These projections will become reality if enough skilled workforces are produced with a high level of broad technical competencies specifically for the automotive environment. This will also require consumer education on AVs that could bring all the comfort and excitement across all segments of the population. This brings a substantial opportunity for the educational sectors in generating the workforce required in AV sectors by enhancing the existing curricula in the areas related to AVs or developing a cross-disciplinary course or capstone project that could expose students with a technical background in computer science, computer engineering, electrical engineering, and mechatronics. Since AV has many technologies involved, it is challenging to design an appropriate curriculum and provide hands-on activities. Small-scale learning kits may be an affordable and effective solution for introductory courses on AVs or for beginners. This paper will discuss the use of those widely available small-scale learning kits, their benefits, and their challenges.

Instruction in an introductory programming course is typically designed to introduce new concepts and to review and integrate the more recent concepts with what was previously learned in the course. Therefore, most exam questions in an introductory programming course require students to write lines of code that contain syntactic elements corresponding to the programming concepts covered during the instruction. This study investigates the number of concepts involved in the exam problems of an introductory Java programming course. In addition, this study compares how the increase in the number of concepts correlates with the ability of students to write error-free lines of code. The instructional method adopted in this study focuses on providing students with a problem-solving schema and a resultant programming plan that integrates many concepts to meet the problem's goal. Results from this study indicate that as the course progresses through the semester, students, on average, apply appropriate problem-solving schemas and programming plans to produce more error-free lines of code, despite an increase in the concept count in the problems. Furthermore, the exam problems later in the course repeat the application of cluster concepts that have appeared in the past exam. This paper illustrates how programming is a cumulative skill and that repeating and building upon the applications of these concept clusters several times through the course increases the likelihood that students will produce more correct lines of code as the semester progresses.

User Experience Design (UXD) is an often-neglected area of the information systems (IS) curriculum. UXD classes specifically designed for IS students are still uncommon in IS programs and this study aims to add to the body of knowledge to prepare a more well-rounded future generation of IS professionals. With this goal in mind, this study describes the redesign of an introductory UXD course following Kolb's learning cycle and constructivist instructional models. This paper describes the implementation of the supporting pedagogy and the opportunity for students to better master core UXD concepts. UXD, a multi-disciplinary area is built on skills learned in systems analysis and design class while students learn to apply relevant concepts through a hands-on, instructor-led, individual, in-class sample project. The skills are then applied by engaging students in active learning in a team setting to deliver value to a local organization by solving related, real-life challenges. Students work on community-engaged team projects to enhance their appreciation of the impact and relevance of their semester-long project deliverable. Constructivism guides the instructional models of the framework, in which problem-based learning is used to help students build and apply relevant skills. The instructional models and implications for instructional design are discussed along with a proposed pedagogical approach, course setting and structure, tools and techniques engaged, student feedback analyzed, and lessons learned.