Visual design and variation of mediums in e-learning resources

Master's thesis Multimedia and Educational Technology MM500 - University of Agder 2017Konfidensiell til / confidential until 01-07-202

Teaching Social Media Analytics: An Assessment Based on Natural Disaster Postings

Unstructured data in social media is as part of the “big data” spectrum. Unstructured data in Social media can provide useful insights into social phenomena and citizen opinions, both of which are critical to government policy and businesses decisions. Teachers of business intelligence and analytics commonly use quantitative data from sales, marketing, finance and manufacturing to demonstrate various analytics concepts in a business context. However, researchers have seldom used social media data to analyze social behavior and communication. In this study we aim to demonstrate an assessment structure for teaching social media analytics concepts with the goal of analyzing and interpreting social media content. We base this assessment on forum postings regarding two recent events: the Christchurch earthquake in New Zealand, and the Japanese earthquake and tsunami. The aim of the assessment is to discover social insights. We base the assessment structure on Cooper’s Analytics Framework to cover such concepts as term frequency (TF), term frequency–inverse document frequency (TFIDF), data visualization, sentiments and opinions analysis, the Nearest Neighbor K-NN classification algorithm, and Information Diffusion theory. We review how the students performed on the assignment that used this assessment, and we make recommendations for future studies

When, how and for whom changes in engagement happen:A transition analysis of instructional variables

The pace of our knowledge on online engagement has not been at par with our need to understand the temporal dynamics of online engagement, the transitions between engagement states, and the factors that influence a student being persistently engaged, transitioning to disengagement, or catching up and transitioning to an engaged state. Our study addresses such a gap and investigates how engagement evolves or changes over time, using a person-centered approach to identify for whom the changes happen and when. We take advantage of a novel and innovative multistate Markov model to identify what variables influence such transitions and with what magnitude, i.e., to answer the why. We use a large data set of 1428 enrollments in six courses (238 students). The findings show that online engagement changes differently —across students— and at different magnitudes —according to different instructional variables and previous engagement states. Cognitively engaging instructions helped cognitively engaged students stay engaged while negatively affecting disengaged students. Lectures —a resource that requires less mental energy— helped improve disengaged students. Such differential effects point to the different ways interventions can be applied to different groups, and how different groups may be supported. A balanced, carefully tailored approach is needed to design, intervene, or support students' engagement that takes into account the diversity of engagement states as well as the varied response magnitudes that intervention may incur across diverse students’ profiles

Reciprocal teaching and its effect on inference skills to enhance reading comprehension

The purpose of this study is to determine how the use of reciprocal teaching affects the learning of inference skills in four, 4th grade excel readers. By utilizing reciprocal teaching as the instructional component and incorporating engaging read alouds, this study seeks to determine how these effect the development of inference skills. The students in this study received explicit instruction about inference skills and the reciprocal teaching model. Students participated in daily read alouds and reciprocal teaching for twenty minutes over the period of four weeks. Through teacher observations, focus group discussions, excerpts from teacher research journal, and video clips the study showed some increase in inference making among focus group participants. Out of four focus group participants, all participants increased their ability to make inferences in reading. The findings of this study suggest that read alouds along with reciprocal teaching, teacher questioning, and reader\u27s schema effect students\u27 development of inference skills in reading

Unravelling the Temporal Process of Learning Design and Student Engagement in Distance Education using Learning Analytics

Designing a curriculum in online and distance education can be challenging because the processes of what, when, and how students study are not always visible to teachers due to the limited opportunities for face-to-face interactions. The aim of this thesis is to explore how teachers design for learning, together with how the learning design impacts upon the students’ actual engagement with the learning materials, with the subsequent effect on their academic performance. One way forward, is to build on the intersection between the most recent work in learning analytics and learning design research. I have therefore argued for and investigated the potential of incorporating the design of learning activities into the analysis of student learning behaviour. On the one hand, the visualisation of learning activities designed by teachers provides the pedagogical context to improve the interpreta-tion of the observed learning behaviour and its effect on academic performance. On the oth-er hand, the analysis of online digital traces of learning activities offers a dynamic account of how students learn in practice in a distance learning environment. As a result, this thesis sheds new light on the implicit process of how learning design influences student engagement in distance education By employing a mixed-method research design, I first examined how teachers design for learning using visualisations and network analysis of 37 modules over 30 weeks at The Open University. In the next step, I conducted an in-depth qualitative investigation with 12 teachers into the underlying factors that influenced their design decisions, as well as the perceived barriers and affordances of adopting approaches from the Open University Learning Design Initiative. The findings revealed common patterns as well as variations in learning design across modules and their disciplines of study. Analysis of the interviews revealed underlying tensions between teachers’ autonomy and the influence of management and institutional policies in the design process and the adoption of learning design tools. After laying out the foundation for understanding the learning design processes, I carried out a large-scale analysis of 37 modules and 45,190 students to examine how learning design influences student engagement, satisfaction, and performance. The findings indicated that learning design explained up to 69% of the variance in student engagement, which was strongly driven by assimilative, assessment, and communication activities. Finally, I conducted a fine-grained analysis exploring the (in)consistencies between learning design and student behaviour and how different engagement patterns impact academic performance. The analysis found misalignments between how teachers designed for learning and how students actually studied. In most weeks, students spent less time studying the assigned materials compared to the number of hours recommended by instructors. High-performing students not only studied ‘harder’ by spending more time, but also ‘smarter’ by engaging in a timely manner. Altogether, this thesis has contributed new scientific insights into the dynamic temporal aspects of how teachers design for learning and the relations between learning design, engagement, and academic performance in distance education. As an implication, the findings reported here demonstrated how learning design could improve the accuracy and interpretability of learning analytics models, and how learning analytics could help teachers identify potential inconsistencies between learning design and student behaviour

Confronting the difficult challenges of academic reading of Indonesian graduate students through the lens of self-efficacy and metacognitive strategies

Students’ self-efficacy and reading strategies have been globally investigated. However, there is a limited number of studies in Indonesia that examined the correlation between self-efficacy and metacognitive reading strategies. This study aimed to find out the correlation between students’ self-efficacy and metacognitive reading strategies, their perceptions of self-efficacy, and their metacognitive strategies. This mixed-method study used a Likert scale questionnaire and interview to collect the data. From the quantitative data analysis, the results show that there is a positive correlation between students’ self-efficacy and metacognitive reading strategies of the Indonesian graduate students, which was significant at the 0.01 level (r = .970, n = 33). The students used the most metacognitive strategies in every stage of reading to a high degree. They also shared different strategies used when students encountered difficulties (St. 5, M=4.12). From the qualitative data analysis, the students applied four different strategies for each reading stage. They also shared the different reasons concerning the use of metacognitive reading strategies. This current study offers one major implication. Since the students’ levels of self-efficacy are affected by extrinsic aspects, teachers need to develop a professional identity that enables them to support students in developing self-beliefs and metacognitive reading strategies