Gamification in higher education and stem : a systematic review of literature

In recent years, gamification, the use of game elements in non-game contexts, has drawn the attention of educators due to the possibility of making learning more motivating and engaging; this led to an increase of research in the field. Despite the availability of literature reviews about gamification and its effects, no work to this date has focused exclusively on Higher Education (HE). Next, worldwide there is an increasing demand for skilled Science, Technology, Engineering and Mathematics (STEM) professionals that meet the challenges related to scientific and technological innovations of the 21st Century. This lead to the need of strengthening STEM Higher Education. This brings us to the purpose of this work: presenting a systematic literature review of empirical studies about gamification STEM related Higher Education. This review study started from a systematic mapping design of 'Web of Science' articles, with following inclusion criteria: empirical gamification studies set up in HE, published between 2000 and 2016; focusing on undergraduate or graduate students; in the STEM knowledge field, and set up in authentic settings. An initial search resulted in 562 potentially relevant articles. After applying all selection criteria, only 18 studies could be retained. 12 additional articles were included by analyzing references from earlier literature reviews, resulting in 30 studies to be included. Analysis results show how a combination of game elements (e.g. leaderboards, badges, points and other combinations) positively affects students' performance, attendance, goal orientation and attitude towards mostly computer science related subjects. The analysis results also point at a lack of studies in certain STEM areas, a lack of studies that identify the particular game element associated with the positive differential impact on student performance; a lack of validated psychometric measurements, and lack of focus on student variables that could/should be taken into account as mediating/moderating variables clarifying the impact of gamification in the HE focus on STEM learning and teaching

Teaching psychology to computing students

The aim of this paper is twofold. The first aim is to discuss some observations gained from teaching Psychology to Computing students, highlighting both the wide range of areas where Psychology is relevant to Computing education and the topics that are relevant at different stages of students’ education. The second aim is to consider findings from research investigating the characteristics of Computing and Psychology students. It is proposed that this information could be considered in the design and use of Psychology materials for Computing students. The format for the paper is as follows. Section one will illustrate the many links between the disciplines of Psychology & Computing; highlighting these links helps to answer the question that many Computing students ask, what can Psychology offer to Computing? Section two will then review some of the ways that I have been involved in teaching Psychology to Computing students, from A/AS level to undergraduate and postgraduate level. Section three will compare the profiles of Computing and Psychology students (e.g. on age, gender and motivation to study), to highlight how an understanding of these factors can be used to adapt Psychology teaching materials for Computing students. The conclusions which cover some practical suggestions are presented in section four

Predicting the academic success of architecture students by pre-enrolment requirement: using machine-learning techniques

In recent years, there has been an increase in the number of applicants seeking admission into architecture programmes. As expected, prior academic performance (also referred to as pre-enrolment requirement) is a major factor considered during the process of selecting applicants. In the present study, machine learning models were used to predict academic success of architecture students based on information provided in prior academic performance. Two modeling techniques, namely K-nearest neighbour (k-NN) and linear discriminant analysis were applied in the study. It was found that K-nearest neighbour (k-NN) outperforms the linear discriminant analysis model in terms of accuracy. In addition, grades obtained in mathematics (at ordinary level examinations) had a significant impact on the academic success of undergraduate architecture students. This paper makes a modest contribution to the ongoing discussion on the relationship between prior academic performance and academic success of undergraduate students by evaluating this proposition. One of the issues that emerges from these findings is that prior academic performance can be used as a predictor of academic success in undergraduate architecture programmes. Overall, the developed k-NN model can serve as a valuable tool during the process of selecting new intakes into undergraduate architecture programmes in Nigeria

Providing behaviour awareness in collaborative project courses

Several studies show that awareness mechanisms can contribute to enhance the collaboration process among students and the learning experiences during collaborative project courses. However, it is not clear what awareness information should be provided to whom, when it should be provided, and how to obtain and represent such information in an accurate and understandable way. Regardless the research efforts done in this area, the problem remains open. By recognizing the diversity of work scenarios (contexts) where the collaboration may occur, this research proposes a behaviour awareness mechanism to support collaborative work in undergraduate project courses. Based on the authors previous experiences and the literature in the area, the proposed mechanism considers personal and social awareness components, which represent metrics in a visual way, helping students realize their performance, and lecturers intervene when needed. The trustworthiness of the mechanisms for determining the metrics was verified using empirical data, and the usability and usefulness of these metrics were evaluated with undergraduate students. Experimental results show that this awareness mechanism is useful, understandable and representative of the observed scenarios.Peer ReviewedPostprint (published version

Providing behaviour awareness in collaborative project courses

Several studies show that awareness mechanisms can contribute to enhance the collaboration process among students and the learning experiences during collaborative project courses. However, it is not clear what awareness information should be provided to whom, when it should be provided, and how to obtain and represent such information in an accurate and understandable way. Regardless the research efforts done in this area, the problem remains open. By recognizing the diversity of work scenarios (contexts) where the collaboration may occur, this research proposes a behaviour awareness mechanism to support collaborative work in undergraduate project courses. Based on the authors previous experiences and the literature in the area, the proposed mechanism considers personal and social awareness components, which represent metrics in a visual way, helping students realize their performance, and lecturers intervene when needed. The trustworthiness of the mechanisms for determining the metrics was verified using empirical data, and the usability and usefulness of these metrics were evaluated with undergraduate students. Experimental results show that this awareness mechanism is useful, understandable and representative of the observed scenarios.Peer ReviewedPostprint (published version

Can a five minute, three question survey foretell first-year engineering student performance and retention?

This research paper examines first-year student performance and retention within engineering. A considerable body of literature has reported factors influencing performance and retention, including high school GPA and SAT scores,1,2,3 gender,4 self-efficacy,1,5 social status,2,6,7 hobbies,4 and social integration.6,7 Although these factors can help explain and even partially predict student outcomes, they can be difficult to measure; typical survey instruments are lengthy and can be invasive of student privacy. To address this limitation, the present paper examines whether a much simpler survey can be used to understand student motivations and anticipate student outcomes. The survey was administered to 347 students in an introductory Engineering Graphics and Design course. At the beginning of the first day of class, students were given a three-question, open-ended questionnaire that asked: “In your own words, what do engineers do?”, “Why did you choose engineering?”, and “Was there any particular person or experience that influenced your decision?” Two investigators independently coded the responses, identifying dozens of codes for both motivations for pursuing engineering and understanding of what it is. Five hypotheses derived from Dweck’s mindset theory7 and others8,9 were tested to determine if particular codes were predictive of first-semester GPA or first-year retention in engineering. Codes that were positively and significantly associated with first-semester GPA included: explaining why engineers do engineering or how they do it, stating that engineers create ideas, visions, and theories, stating that engineers use math, science, physics or analysis, and expressing enjoyment of math and science, whereas expressing interest in specific technical applications or suggesting that engineers simplify and make life easier were negatively and significantly related to first-semester GPA. Codes positively and significantly associated with first-year retention in engineering included: stating that engineers use math or that engineers design or test things, expressing enjoyment of math, science, or problem solving, and indicating any influential person who is an engineer. Codes negatively and significantly associated with retention included: citing an extrinsic motivation for pursuing engineering, stating that they were motivated by hearing stories about engineering, and stating that parents or family pushed the student to become an engineer. Although many prior studies have suggested that student self-efficacy is related to retention,1,5 this study found that student interests were more strongly associated with retention. This finding is supported by Dweck’s mindset theory: students with a “growth” mindset (e.g., “I enjoy math”) would be expected to perform better and thus be retained at a higher rate than those with a “fixed” mindset (e.g., “I am good at math”).7 We were surprised that few students mentioned activities expressly designed to stimulate interest in engineering, such as robotics competitions and high school engineering classes. Rather, they cited general interests in math, problem solving, and creativity, as well as family influences, all factors that are challenging for the engineering education community to address. These findings demonstrate that relative to its ease of administration, a five minute survey can indeed help to anticipate student performance and retention. Its minimalism enables easy implementation in an introductory engineering course, where it serves not only as a research tool, but also as a pedagogical aid to help students and teacher discover student perceptions about engineering and customize the curriculum appropriately

On the domain-specificity of mindsets: The relationship between aptitude beliefs and programming practice

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Deliberate practice is important in many areas of learning, including that of learning to program computers. However, beliefs about the nature of personal traits, known as mindsets, can have a profound impact on such practice. Previous research has shown that those with a fixed mindset believe their traits cannot change; they tend to reduce their level of practice when they encounter difficulty. In contrast, those with the growth mindset believe their traits are flexible; they tend to maintain regular practice despite the level of difficulty. However, focusing on mindset as a single construct focused on intelligence may not be appropriate in the field of computer programming. Exploring this notion, a self-belief survey was distributed to undergraduate software engineering students. It revealed that beliefs about intelligence and programming aptitude formed two distinct constructs. Furthermore, the mindset for programming aptitude had greater utility in predicting software development practice, and a follow-up survey showed that it became more fixed throughout instruction. Thus, educators should consider the role of programming-specific beliefs in the design and evaluation of introductory courses in software engineering. In particular, they need to situate and contextualize the growth messages that motivate students who experience early setbacks

Evaluating the Weekly-Assessed Tutorial Sheet approach to assessment: background, pedagogy and impact

This paper presents the results of using student-unique, weekly-assessed tasks to overcome a low examination performance in a first-year engineering module. In this instance, the weekly assessment tasks were created by off-the-shelf and bespoke software to form an integrated computer-assisted assessment (CAA) programme. This programme set, delivered, collected, marked and provided prompt feedback on the students’ work. The CAA was a set of student-unique Weekly-Assessed Tutorial Sheets (WATS). The rationale for the modified assessment strategy is presented together with the examination performance figures before and after the introduction of WATS.Peer reviewe