Introductory programming: a systematic literature review

As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research

Dealing with a Missing Sensor in a Multilabel and Multimodal Automatic Affective States Recognition System

Data from multiple sensors can boost the automatic recognition of multiple affective states in a multilabel and multimodal recognition system. At any time, the streaming from any of the contributing sensors can be missing. This work proposes a method for dealing with a missing sensor in a multilabel and multimodal automatic affective states recognition system. The proposed method, called Hot Deck using Conditional Probability Tables (HD-CPT), is incorporated into a multimodal affective state recognition system for compensating the loss of a sensor using the recorded historical information of the sensor and its interaction with the other available sensors. In this work, we consider a multilabel classifier, named Circular Classifier Chain, for the automatic recognition of four states: tiredness, anxiety, pain, and engagement; combined with a multimodal classifier based on three sensors: fingers pressure, hand movements, and facial expressions; which was adapted for coping with the problem of a missing sensor in a virtual rehabilitation platform for post-stroke patients. A dataset of five post-stroke patients who attended ten longitudinal rehabilitation sessions was used for the evaluation. The inclusion of HD-CPT compensated for the loss of one sensor with results above those obtained with only the remaining sensors available. HD-CPT prevents the system from collapsing when a sensor fails, providing continuity of operation with results that attenuate the loss of the sensor. The proposed method HD-CPT can provide robustness for the naturalistic everyday use of an affective states recognition system

Students’ Preferences Between Traditional and Video Lectures: Profiles and Study Success

Peer reviewe

Education Research Using Data Mining and Machine Learning with Computer Science Undergraduates

In recent decades, we are witness to an explosion of technology use and integration of everyday life. The engine of technology application in every aspect of life is Computer Science (CS). Appropriate CS education to fulfill the demand from the workforce for graduates is a broad and challenging problem facing many universities. Research into this ‘supply–chain’ problem is a central focus of CS education research. As of late, Educational Data Mining (EDM) emerges as an area connecting CS education research with the goal to help students stay in their program, improve performance in their program, and graduate with a degree. We contribute to this work with several research studies and future work focusing on CS undergraduate students relating to their program success and course performance analyzed through the lens of data mining. We perform research into student success predictors beyond diversity and gender. We examine student behaviors in course load and completion. We study workforce readiness with creation of a new teaching strategy, its deployment in the classroom, and the analysis shows us relevant Software Engineering (SE) topics for computing jobs. We look at cognitive learning in the beginning CS course its relations to course performance. We use decision trees in machine learning algorithms to predict student success or failure of CS core courses using performance and semester span of core curriculum. These research areas refine pathways for CS course sequencing to improve retention, reduce time-to–graduation, and increase success in the work field

Video-Based Instruction For Introductory Computer Programming

Video replacement of in-­person lecture is finding its way into more and more computer science education settings such as inverted classrooms, massive open online courses, online/distance learning, and programming camps. Since the use of video is critical to some pedagogies, the question of how it impacts student attitudes and learning is important. This study investigates this by looking at experiences in the programming unit within two sections of a broad-­scope CS0 course, one of which used video-­based instruction while the other did not. We found that students in the video section had a more positive view of the learning activities and thought their student-­instructor interactions were more meaningful. Student performance data also suggests that video instruction may benefit student learning as well

Second level computer science: The Irish K-12 journey begins

This paper initially describes the introduction of a new computer science subject for the Irish leaving certificate course. This is comparable to US high school exit exams (AP computer science principals) or the UK A level computer science. In doing so the authors wish to raise international awareness of the new subject’s structure and content. Second, this paper presents the current work of the authors, consisting of early initiatives to try and give the new subject the highest chances of success. The initiatives consist of two facets: The first is the delivery of two-hour computing camps at second level schools (to address stereotypes and provide insight on what computer science really is), which was delivered to 2,943 students, in 95 schools between September 2017 and June 2018. Second, the authors followed this with teacher continual professional development (CPD) sessions, totalling 22, to just over 500 teachers. Early findings are presented, showing potentially concerning trends for gender diversity and CPD development. A call is then raised, to the international computer science education community for wisdom and suggestions that the community may have developed from prior experience. This is to obtain feedback and recommendations for the new subject and the authors’ current initiatives, to address early concerns and help develop the initiatives further