Abstract: Technological innovations such as blended learning (BL) are rapidly changing teaching and learning in higher education, where BL integrates face to face teaching with web based learning. Thus, as polices related to BL increases, it is required to explore the theoretical foundation of BL studies and how BL were adopted and implemented in relation to students, lecturers and administration. However, only fewer studies have focused on exploring the constructs and factors related to BL adoption by considering the students, lecturers and administration concurrently. Likewise, prior research neglects to explore what practices are involved for BL implementation. Accordingly, this study systematically reviews, synthesizes, and provides meta-analysis of 94 BL research articles published from 2004 to 2020 to present the theoretical foundation of BL adoption and implementation in higher education. The main findings of this study present the constructs and factors that influence students, lecturers and administration towards adopting BL in higher education. Moreover, findings suggest that the BL practices to be implemented comprises of face-to-face, activities, information, resources, assessment, and feedback for students and technology, pedagogy, content, and knowledge for lecturers. Besides, the review reveals that the ad hoc, technology acceptance model, information system success model, the unified theory of acceptance and use of technology, and lastly diffusion of innovations theories are the mostly employed theories employed by prior studies to explore BL adoption. Findings from this study has implications for student, lecturers and administrators by providing insights into the theoretical foundation of BL adoption and implementation in higher education.

Abstract: The aim of this research is to determine the effects of Scratch and Alice tools and programming teaching practices on student engagement, reflective thinking and problem-solving skills and computational thinking (CT) comparatively. A quasi-experimental design was used in the research and patterns with pretest–posttest control group were chosen for the variables. The study group was compromised of 110 students at 5th grade in 2016 spring semester. 1st and 2nd groups of Computing Technologies Course have been assigned objectively. Alice programming tool was preferred in the learning process of the 1st experimental group, whereas, Scratch programming tool was utilised in the 2nd study group during application process which lasted for 8 weeks. Results of the research show that programming teaching with Scratch has affected engagement and reflective thinking skills of the students for problem solving more positively than Alice. It has been stated that teaching with Alice affects skills related to CT of the students positively. Furthermore, some recommendations have been made for the future researches.

Abstract: It is argued that learning management systems (LMS) are mainly used for formal and informal learning at the expense of non-formal learning. This ignites reluctance in students to use LMS to their maximum potential in institutions of higher education (IHE). Through two contrasting qualitative case studies in two IHEs, ways in which LMS can be used for non-formal learning are proposed. Data were generated using reflective activities, Zoom group meetings and one-on-one semi-structured interviews with 31 students who were purposively and conveniently sampled from teacher education programmes at a South African and an American university. The theoretical framework of connectivism was used as a lens to make meaning of data that were thematically analysed. Findings suggest that students did not have a love of using LMS but used the Moodle and Canvas LMS primarily for downloading readings and participating in discussion forums. The study therefore, proposes a non-formal learning framework for self-direction, and concludes that ignoring students’ personal (non-formal) experiences which stimulate a love of using LMS may result in IHE to needing to change from one LMS to another.

Abstract: The purpose of this study was to combine the results of the experimental studies conducted between the years of 2000–2018 examining the effect of game-based learning method on the academic achievement of students through a meta-analysis. In this study addressing the effect of game-based learning method on the academic achievement of students, meta-analysis included 38 studies which had been issued in the databases of Google Academic and National Thesis Center of Turkish Council of Higher Education between 2010 and 2018 and selected according to certain criteria. The study also involved subgroup analyses in addition to revealing the overall effect of game-based learning on academic achievement. According to the research findings, it is possible to allege that Hedges g value which was estimated to be 1.695 for the overall effect size of game-based learning on student achievement indicates a wide-ranging effect. Furthermore, as a result of the analyses, it was revealed that the effect of game-based learning on the academic achievement of students does not differ according to the sub-dimensions of the levels of schooling, the different types of reporting and various disciplines.

Abstract: Delivery of blended-mode eLearning programs is challenging due to a range of factors, including motivational and engagement issues. This is more challenging in the context of Technical and Vocational Education and Training (TVET), which aims to develop competencies to empower learner to find gainful employment. This study proposes an operational model and gamification design to develop blended eLearning programs, which embed motivational and engagement designs as an effective means of achieving learner success in the TVET context. The motivational design uses a motivational framework with the factors of attention, relevance, confidence, and satisfaction. The engagement design includes behavioural, emotional, and cognitive aspects for enhancing learning. Accordingly, appropriate game dynamics, mechanics, and components are used to gamify a blended eLearning course. This gamification design and operational model could be used as a tool to gamify and deliver the competency-based educational programs, using the blended eLearning approach. The study proposes fifteen game dynamics, relevant mechanics, and appropriate game components. The design utilises structural and content gamification in a sample online course, deploying an open-source learning management system. Furthermore, the study suggests embedding game components at the implementation stage of providing learning opportunities, to motivate and engage learners, thereby achieving the acquisition of expected competencies. The gamified course will be delivered to a selected group of learners in the TVET context to assess the feasibility and viability of this approach in anticipation of the future work.

Abstract: Despite the existence of many programs and training projects in the field of ICT, in post-secondary education, the teaching and learning process continues to be supported by traditional classroom methods. This phenomenon can be particularly observed in education degrees, even though future teachers are expected to acquire the necessary digital skills in order to carry out their work properly. The purpose of this study is to explore in greater depth the use of 2.0 applications in the education training of future teachers, as well as to outline the different correlations between the use of these 2.0 tools and their perceived level of digital competence, age and their level of motivation. For it, a quasi-experimental, ex post facto research was carried out with a sample of 108 future teachers from the Faculty of Education, Pontifical University of Salamanca (UPSA). The results have shown that future teachers have a low level of attitude of use towards ICT in the classroom, with an average of 2.29 based on five points. Furthermore, the results have revealed that the level of digital competence and the motivation to use ICT are two variables that correlate positively, while other variables do not show any correlation, such as age.

Abstract: There is a growing interest in the use of learning analytics in higher education institutions. Learning analytics also appear to have the potential to be used to provide personalized feedback and support in online learning. However, when the literature is examined, the use of learning analytics for this purpose appears as a gap to be investigated. This research aims to examine the opinions of pre-service teachers about the personalized recommendation and guidance feedback based on learning analytics. The research was carried out on 40 pre-service teachers in the Computer I course, which was conducted according to the flipped learning model for 12 weeks. Throughout the research process, personalized feedback based on learning analytics was provided by researcher (the researcher is also the teacher of the Computer I course) to pre-service teachers at the end of each week. Accordingly, the students’ weekly learning management system (LMS) obtained learning analytics results from the log data related to their usage behavior. Then, the researcher prepared personalized recommendation and guidance messages based on learning analytics results. Learning analytics results and related recommendations and guidance messages were sent via LMS (from the messaging tool) as feedback. This process was done for each pre-service teacher by the researcher every week during the research process. The data of the research were obtained with a semi-structured opinion form and content analysis was made in the analysis of the data. As a result of the research, beneficial aspects and limitations of personalized recommendation and guidance feedback based on learning analytics from the perspective of pre-service teachers were revealed. In line with the results obtained from the research, various suggestions were made for the design and use of feedback messages based on learning analytics.

Abstract: Blended forms of learning have become increasingly popular. However, it remains unclear under what circumstances blended learning environments are successful. Studies suggest that blended learning challenges learners’ self-regulation. Yet little is known about what self-regulatory behaviour learners exhibit in such environments. This limited understanding is problematic since this insight is needed for effective designs. Therefore, the aim of this study was to identify learners’ self-regulatory behaviour profiles in blended learning environments and to relate them to designs of blended learning environments. Learners’ (n = 120) self-regulatory behaviour in six ecologically valid blended learning courses was captured. Log files were analysed in a learning analytics fashion for frequency, diversity, and sequence of events. Three main user profiles were identified. The designs were described using a descriptive framework containing attributes that support self-regulation in blended learning environments. Results indicate fewer mis-regulators when more self-regulatory design features are integrated. These finding highlights the value of integrating features that support self-regulation in blended learning environments.

Abstract: This long-term single group study was conducted with pre-service special education elementary teachers taking a required graduate level course on integrating technology into mathematics and science instruction in a New York City public University. The purpose of this study was to explore whether Technological Knowledge (TK), Pedagogical Knowledge (PK), Content Knowledge in mathematics and science (CKM and CKS) and Technological Pedagogical Content Knowledge (TPACK) are independent constructs in the TPACK framework and to develop instruments for assessment of each basic domain of the theoretical TPACK framework. Exploratory and confirmatory factor analyses of the developed instruments suggest that the TPACK construct is independent from TK, PK, CKM and CKS. Further analysis using multiple linear regression showed that TK, PK, and CK are not predictors of TPACK. These findings provide an opportunity for independent assessment of different types of teacher knowledge defined by the TPACK framework. This could help teacher preparation programs to evaluate effectiveness of courses that prepare teachers for integration of technology.

Abstract: The tremendous growth of educational institutions’ electronic data provides the opportunity to extract information that can be used to predict students’ overall success, predict students’ dropout rate, evaluate the performance of teachers and instructors, improve the learning material according to students’ needs, and much more. This paper aims to review the latest trends in predicting students’ performance in higher education. We provide a comprehensive background for understanding Educational Data Mining (EDM). We also explain the measures of determining academic success and highlight the strengths and weaknesses of the most common data mining (DM) tools and methods used nowadays. Moreover, we provide a rich literature review of the EDM work that has been published during the past 12 years (2007–2018) with focus on the prediction of academic performance in higher education. We analyze the most commonly used features and methods in predicting academic achievement, and highlight the benefits of the mostly used DM tools in EDM. The results of this paper could assist researchers and educational planners who are attempting to carry out EDM solutions in the domain of higher education as we highlight the type of features that the previous researches found to have significant impact on the prediction, as well as the benefits and drawbacks of the DM methods and tools used for predicting academic outcomes.

Abstract: Technology integration into post-secondary education may enhance curriculum delivery and student learning experiences. However technology integration also requires faculty to adapt current teaching practices. Many factors contribute to faculty members’ successful integration of technology into curriculum. In fall 2013, the Bachelor of Science in Nursing and Doctor of Nursing Practice programs at one Midwestern university adopted the use of iPads by students and faculty. Four years after implementation, college leadership wanted to understand faculty members’ perception of the change. Therefore the purpose of this study was to explore faculty perceptions of what factors influenced iPads integration into curriculum. Investigators collected data from fourteen faculty members during two targeted focus groups. Two investigators analyzed transcripts of the focus group recordings using content analysis. Results yielded three major domains of factors: student attributes, faculty attributes, and device capabilities. Each domain provided unique factors viewed by faculty as influencing the success of technology integration. In addition, some factors were shared between domains - demonstrating interconnectedness. While faculty members identified key factors influencing successful technology implementation, results also uncovered challenges. Lessons learned, suggestions to address modifiable factors in the future, and recommendations for programs considering technology implementation are presented.

Abstract: With the increase of mobilized and relatively inexpensive technologies, educators are challenged to consider new innovations for learning situations. This case study evaluates the use of mobile learning in a college course for instructional purposes. The study describes the specific manner in which mobile technology was utilized and then details ways student learning was impacted. The current body of literature regarding m-learning reveals a need for theoretical and pedagogical basis for m-learning within an educational context. Thus, the author developed an assessment tool to examine the use of mobile technology in a higher education course. This article reinforces m-learning should be based upon established course goals and objectives and not a particular type of electronic device. The researchers report the use of mobile technology use in this case study enhanced multiple types of learning, including, but not limited to, experiential, place-based, field-based, active, authentic, self-regulated and hands-on learning.

Abstract: High attrition rates in online workforce training and development programs suggest that practitioners continue to struggle to develop relevant learner-centric experiences for their workforce. One strategy to increase learner engagement and make training more relevant is through personalizing learning. While there are several efforts to understand personalized learning within K-12 and higher education contexts, there are few published studies that focus on the use of personalized learning within workforce education. In this qualitative study, leaders in training and development (N = 10) were interviewed to uncover (a) the current operating definition of personalized learning, (b) whether or not personalized learning initiatives are occurring within the workplace setting, and (c) what obstacles exist in implementing personalized learning as well as (d) what opportunities for personalized learning exist from an organizational standpoint. Design and implementation considerations for future programs, resources, or tools that incorporate personalized learning as a learning strategy in online workforce training and development are discussed.

Abstract: This study designed a science course following collaborative problem solving (CPS) processes, and examined the effect on students’ CPS awareness. The Limnic Eruption CPS course was implemented using a Moodle system in a tenth-grade class. Considering the complex and coordinated nature of CPS, in order to improve CPS skills, it is important to identify what are related with the development of all sub-skills of CPS. Thus this study aimed to determine potential factors that affect the use of CPS skills in students’ motivational and behavioral dimensions. Multiple data sources including learning tests, questionnaire feedback, and learning logs were collected and examined by learning analytics approach. The relationships between students’ CPS awareness with their learning motivation and learning behaviors were explored. The research findings indicated a significant positive correlation between CPS awareness and certain learning motivation factors and learning behavior factors. Considering the students’ individual differences in learning abilities, we also compared the results of high and low performance groups. As a result, low performers’ learning motivation and learning behaviors were correlated with the social domain of CPS awareness, while those of high performers were correlated with their cognitive awareness.

Abstract: This emerging technology report explores three-dimensional collaborative virtual learning environments (3D CVLEs) as an intervention modality with potential to foster development of knowledge and skills for people with autism spectrum disorder (ASD) Affordances and unique characteristics of 3D CVLEs are detailed and considered from the perspectives of learning, instruction, and assessment Research suggests that 3D CVLEs can promote acquisition of social and communicative competencies for individuals with ASD in a safe and controllable manner However, substantial challenges still exist related to overexposure and cybersickness This report provides an analysis of current trends in the field, along with considerations of relevance and integration challenges with this unique learner population Implications for further research are discussed

Abstract: Higher-level learning goals can be achieved almost only through teaching methods which actively involve students in their learning. This study aimed to compare the effects of traditional teaching and flipped classroom methods on midwifery students’ practical learning. This embedded mixed method study was conducted on 34 first-year midwifery students in 2017–2018 academic year in Babol city (one of the largest cities in northern Iran). The contents of the four sessions of a course called the principles and techniques of midwifery were prepared for both flipped classroom and traditional teaching methods and provided to students using the crossover design. All students were selected by census and randomly divided into two groups. The students’ attitudes towards both teaching methods were assessed at the beginning and also the end of the study intervention, while their satisfaction, knowledge and practice were assessed one month after intervention. In the second phase (qualitative study), the student's perspective about the weaknesses and the strengths of the both teaching methods were explored using the open-ended questions. Quantitative data were analyzed using SPSS and qualitative data with conventional content analysis. Flipped classroom method was significantly more effective than traditional teaching in improving midwifery students’ knowledge and practice. They also had significantly better attitude and more satisfaction with it (P < 0.05). The strengths of flipped classroom were promotion of learning, consolidation of learning, unlimited opportunity for learning, and interactive learning. This study suggests that flipped classroom method promotes practical learning and leads to positive learning among the midwifery students.

Abstract: This article describes designs that use multiple conversational agents within the framework of intelligent tutoring systems. Agents in this case are computerized talking heads or embodied animated avatars that help students learn by performing actions and holding conversations with them in natural language. The earliest conversational intelligent tutoring systems were limited to a single agent that interacted with a student in the role of a teacher or expert. Technological advances have since made possible systems in which multiple agents interact with the learner and each other to model ideal behavior, strategies, reflections, and social interactions. Though still an emerging technology, multi-agent intelligent tutoring systems afford pedagogical benefits that go beyond the capabilities of the single-agent system and have facilitated learning gains on a variety of subject matters and skills, including science, technology, engineering, mathematics, research methods, metacognition, and language comprehension. The present work describes some common multi-agent designs that may be used to achieve a variety of pedagogical goals. We provide examples of how these designs have been implemented in educational or experimental settings and anticipate future use within the field of artificial intelligence.

Abstract: This research examined the contribution of an online collaborative program involving students from two different teacher training colleges. It measured the impact of the program on attitudes towards technology with regard to technological anxiety, self-confidence and technological liking among students. The advanced online collaborative program at the training colleges was based on a model that used technology to increase trust between students from different cultures through online learning. The research was qualitative and was based on 58 graduate students who participated in the program. The questionnaires answered by participants dealt with the level of collaboration, intrinsic motivation, satisfaction, and attitudes towards technology. The results indicate that in an online collaborative program the student’s intrinsic motivation is affected by the level of his/her satisfaction, and this affects his/her attitudes towards technology when this is the only course for enhancing technology in education. The most significant contribution is to the liking of the use of advanced technologies, then to the self-confidence in using technology, and finally to decreasing the anxiety of technology.

Abstract: The current study investigated change readiness for smartphone technology among 610 secondary school teachers in Kuwait. We assessed teachers’ readiness to adopt smartphones as instructional tools, with respect to their personal concerns, technological competency and personal characteristics. We implemented a quantitative survey design, administering two questionnaires to all participants: the Stages of Concern Questionnaire (SoCQ), based on the concerns-based adoption model, and a newly developed SmartPhone Competency Scale. The findings indicated that teachers’ perceptions of the adoption of smartphone technology were associated with their stages of concern and smartphone competency level. Scores on the six stages of concern were compared. Concerns were greatest at the personal stage and lowest at the management stage. In addition, teachers with moderate levels of teaching experience (5–10 years) and teachers who specialized in the sciences reported stronger management concerns than teachers specializing in the arts. The five stages of concern with the highest scores (informational, personal, consequences, collaboration, and refocusing) were positively and significantly correlated with the four smartphone competencies. These results suggest that the SoCQ is a practical tool with predictive value for assessing teachers’ change readiness for the adoption of smartphone technology.

Abstract: The current study investigated predictors of shallow versus deep learning within a serious game known as Operation ARA. This game uses a myriad of pedagogical features including multiple-choice tests, adaptive natural language tutorial conversations, case-based reasoning, and an E-text to engage students. The game teaches 11 topics in research methodology across three distinct modules that target factual information, application of reasoning to specific cases, and question generation. The goal of this investigation is to discover predictors of deep and shallow learning by blending Evidence-Centered Design (ECD) with educational data mining. In line with ECD, time-honored cognitive processes or behaviors of time-on-task, discrimination, generation, and scaffolding were selected because there is a large research history supporting their importance to learning. The study included 192 college students who participated in a pretest-interaction-posttest design. These data were used to discover the best predictors of learning across the training experiences. Results revealed distinctly different patterns of predictors of deep versus shallow learning for students across the training environments of the game. Specifically, more interactivity is important for environments contributing to shallow learning whereas generation and discrimination is more important in training environments supporting deeper learning. However, in some training environments the positive impact of generation may be at the price of decreased discrimination.

Abstract: As a digital learning medium, serious games can be powerful, immersive educational vehicles and provide large data streams for understanding player behavior. Educational data mining and learning analytics can effectively leverage big data in this context to heighten insight into student trajectories and behavior profiles. In application of these methods, distilling event-stream data down to a set of salient features for analysis (i.e. feature engineering) is a vital element of robust modeling. This paper presents a process for systematic game-based feature engineering to optimize insight into player behavior: the IDEFA framework (Integrated Design of Event-stream Features for Analysis). IDEFA aligns game design and data collection for high-resolution feature engineering, honed through critical, iterative interplay with analysis. Building on recent research in game-based data mining, we empirically investigate IDEFA application in serious games. Results show that behavioral models which used a full feature set produced more meaningful results than those with no feature engineering, with greater insight into impactful learning interactions, and play trajectories characterizing groups of players. This discovery of emergent player behavior is fueled by the data framework, resultant base data stream, and rigorous feature creation process put forward in IDEFA—integrating iterative design, feature engineering, and analysis for optimal insight into serious play.

Abstract: The goal of this study is to identify the relationship between K-12 teachers’ self-efficacy beliefs, classroom goal structure and use of instructional strategies. The study also aims to determine if there is variance in the relationship between these constructs for primary versus secondary school teachers. Data collection involved completion of a self-report survey by 810 primary and secondary school teachers in Thailand. Results revealed that personal and ICT teaching self-efficacy directly predicted both mastery and performance classroom goal structures for K-12 teachers. Mastery classroom goal structure predicted deep learning. Performance classroom goal structure predicted surface learning. ICT teaching self-efficacy was the strongest predictor of teachers’ instructional strategies with ICTs. Results also revealed that primary teachers’ performance classroom goal structure was positively associated with the use of deep-learning strategies with ICTs and student-centered learning with ICTs. In contrast, for secondary teachers, mastery classroom goal structure was positively associated with student-centered learning with ICTs, whereas both mastery and performance classroom goal structures were positively associated with the use of deep-learning strategies with ICTs. Results of this study suggest that classroom goal structure may be different for ICT classrooms than for regular classrooms. Implications relate to the need to help teachers design ICT activities that reflect both performance and mastery classroom goal structures.

Abstract: This study investigated teachers’ views of Massive Open Online Courses (MOOCs). The sample consisted of 30 teachers recruited from different cities of Turkey using criteria sampling. Phenomenology was the research method of choice. Data were collected using a semi-structured interview form and analyzed using content analysis. Participants use MOOCs because they are free of charge and have good content and high quality. MOOCs help them learn science, technology, engineering, and mathematics, gain professional knowledge, and develop skills, and positive attitudes and values. Most participants are interested in integrating MOOCs in their classes; however, they face various problems during MOOCs, such as loss of motivation and Internet connection issues. It is recommended that MOOCs be designed in such a way that they increase participants’ motivation and allow for feedback.

Abstract: Primary school students have trouble grasping concepts related to plants. Their misconceptions are also notable. On the other hand, mobile devices (such as tablets) and their apps, are considered effective educational tools. For examining whether the same holds true in relation to plants, we carried out a project, having as a target-group 263 students aged 11–12, divided into five groups. Two were taught using printed material, one using laptops and webpages, while the last two were taught using tablets (one with a commercial app and one with a tailor-made one). We chose Bybee’s 5Es as the teaching framework for all groups except the first, in which lecturing was applied. Six two-hour sessions were allocated in each group. We collected data through evaluation sheets and a questionnaire. The results suggested that students in the tablets groups established a solid base of declarative and procedural knowledge regarding plants. Their misconceptions were eased, at least when compared with the groups that used printed material. We also observed a positive impact on motivation and enjoyment. On the basis of the findings, we recommend the active involvement of teachers in the development of apps and the corresponding learning material, so as to be able to gain valuable insights on how mobile learning is implemented. We also propose a teaching framework that would allow the full exploitation of mobile devices’ advantages.

Abstract: This study presents the use of automated data analysis procedures in the teaching-learning process, mediated by telematics platforms. It is based on the application of the principles of virtual learning, the use of the Internet and the automation of data analysis of information collected in Moodle. The application of analysis procedures for the assessment of music competences is proposed based on the data collected in an exam administered at the end of the course. The sample of the study consists of 1327 students (n = 1327) in the first year of Compulsory Secondary Education in Spain and measures the level of acquisition of the key competences denominated “cultural and artistic”. The results are subjected to the K-means classification technique. This technique is used to obtain homogeneously distributed conglomerates which allow for an objective evaluation of the levels of acquisition of the key musical competences.

Abstract: This study aimed to assess the association of smartphone addiction with domains of the big five personality traits (i.e., extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience) after controlling for individual differences such as age, gender, and amount of daily smartphone and internet use. The study employed a cross-sectional survey design, with data gathered from 494 university students using the Turkish adaptation of the Big Five Inventory and Smartphone Addiction Scale. Hierarchical multiple linear regression analyses were applied in order to test two hypotheses. The study put forth that after controlling for the individual differences, the big five personality traits were found to significantly predict smartphone addiction. Agreeableness and conscientiousness were shown to be negative predictors, neuroticism was a positive predictor, and extraversion and openness to experience were not found to be significant predictors. The results of the study are discussed, and some implications are suggested, with revealing the relationship between personality traits and smartphone addiction aiming to help policymakers and practitioners in designing awareness raising activities in schools.

Abstract: This case study focused on the robotics learning process of Mark (a pseudonym), a Latino-American second grader diagnosed with autism spectrum disorder. Drawing on Polanyi’s (Personal knowledge: towards a post-critical philosophy [Kindle version], 1958/2015) notion of “tacit knowing” and “dwelling in tools,” we attempted to understand Mark’s unique processes and ways of engaging in learning about a Light Sensor by pursuing two research questions: (a) How does Mark, with his unique behavioral and socio-emotional characteristics, engage in the robotics class? (b) What insights can we gain from his inquiry as we develop responsive robotics education? Findings revealed that Mark used a non-sequential inquiry process filled with repetitive free explorations and unexpected expanded inquiries about the Light Sensor. This non-sequential inquiry process highlighted that dwelling with robotic manipulatives was Mark’s distinct ways of exploring the Light Sensor. His non-sequential inquiry process emerged from his tacit engagement and expanded to his sophisticated and holistic understanding of the Light Sensor. We discuss implications for a robotics education program that is responsive to young children with diverse needs and characteristics.

Abstract: The purpose of this study was to discuss the influence of the use of tablets and mobile learning in post-secondary education and their impact on the emotions and affects felt by a teacher and students and on their identity constitution. Assemblage theory was the onto-epistemological perspective in which this investigation was grounded, and assemblage ethnography was the methodology used to collect data. An ethnographic account was provided based on what was observed during lessons, and was analysed using the concepts of emotions, affects and subjectivation. Findings indicated that no contradictory emotions and affects emerged as a result of the actions and interactions of components in the assemblage. There was a smooth relationship among human components, influencing the way they see each other and their roles. However, regarding human and non-human components, the affects and emotions that emerged impacted each other, causing tensions between these components.

Abstract: One way to use formative feedback to increase student engagement is through a student response system (SRS). Originally appearing as classroom “clickers,” very little literature exists concerning the ease of use, usefulness and integration, and overall satisfaction of current SRS software smartphone applications. Using the technology acceptance model as a guide, this study uses a mixed methods approach concerning student perceptions of three distinct SRS used in multiple sections of a university undergraduate statistics course. The quantitative results demonstrated significant differences between SRS, while follow-up qualitative questions clarified the Likert-scale data. “All else being equal, the easier system is to interact with, the less effort needed to operate it, the more effort one can allocate the other activities” (Davis 1989, p. 334). With all data considered, students preferred the Socrative app over both TopHat and Learning Catalytics.