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Research in Learning Technology
Journal Prestige (SJR): 0.784
Citation Impact (citeScore): 2
Number of Followers: 246  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2156-7069 - ISSN (Online) 2156-7077
Published by Association for Learning Technology Homepage  [1 journal]
  • E-learning educational atmosphere measure (EEAM): a new instrument for
           assessing e-students’ perception of educational environment

    • Authors: Atekeh Mousavi, Aeen Mohammadi, Rita Mojtahedzadeh, Mandana Shirazi, Hamed Rashidi
      Abstract: Universities assess their academic learning environment to improve students’ learning. Students’ experience in e-learning environment is different from face-to-face educational environment. So, in this study a specific valid and reliable instrument was devised for assessing perception of e-students from educational environment, that is, educational atmosphere. Firstly, we devised the primary instrument based on factors constituting educational atmosphere. Then Instrument’s content and construct validity were assessed. Also, Cronbach’s alpha and test–retest were used for studying the internal consistency and reliability of the instrument respectively. The final instrument named ‘e-learning educational atmosphere measure’ (EEAM) consisted of 40 items covering six factors, including programme effectiveness, teaching quality, ethics and professionalism, learner support, safety and convenience, and awareness of the rules, which accounted for 68.53% of variances. Content validity ratio was more than 0.51 and content validity index score of all questions was above 0.81. Test–retest reliability was 0.85 (p = 0.001) and Cronbach’s alpha was 0.943. Assessing educational atmosphere in e-learning settings by EEAM could provide managers and investors with useful information to settle an effective education system by prioritising the necessary changes.
      PubDate: 2020-01-21
      DOI: 10.25304/rlt.v28.2308
      Issue No: Vol. 28 (2020)
       
  • Analysing construction student experiences of mobile mixed reality
           enhanced learning in virtual and augmented reality environments

    • Authors: Nikolche Vasilevski, James Birt
      Abstract: Mixed reality (MR) and mobile visualisation methods have been identified as important technologies that could reimagine spatial information delivery and enhance higher education practice. However, there is limited research on the impact of mobile MR (MMR) within construction education and improvement of the learners’ experience. With new building information modelling (BIM) workflows being adopted within the architecture, engineering and construction industry, innovative MMR pedagogical delivery methods should be explored to enhance this information-rich spatial technology workflow. This paper outlines qualitative results derived through thematic analysis of learner reflections from two technology-enhanced lessons involving a lecture and a hands-on workshop focussed on MMR-BIM delivered within postgraduate construction education. Seventy participants across the two lessons recruited from an Australian university participated to answer the research question: ‘Does applied mobile mixed reality create an enhanced learning environment for students'’ The results of the analysis suggest that using MMR-BIM can result in an enhanced learning environment that facilitates unique learning experiences, engagement and motivation. However, the study outcome suggests that to understand the processes leading to these learning aspects, further empirical research on the topic is required. This paper is part of the special collection Mobile Mixed Reality Enhanced Learning edited by Thom Cochrane, James Birt, Helen Farley, Vickel Narayan and Fiona Smart. More papers from this collection can be found here.
      PubDate: 2020-01-16
      DOI: 10.25304/rlt.v28.2329
      Issue No: Vol. 28 (2020)
       
  • Patterns in students’ usage of lecture recordings: a cluster
           analysis of self-report data

    • Authors: Daniel Ebbert, Stephan Dutke
      Abstract: Students’ usage of lecture recordings can be characterised by usage frequency, repetitiveness and selectivity in watching, lecture attendance, and social context and location in which students watch the lecture recordings. At the University of Münster (Germany), the lecture recording service was evaluated over three semesters. The data were combined and used for a cluster analysis with the aim of being able to describe the students’ distinct usage patterns. The cluster analysis was performed using partitioning around medoids with Gower distance. Five clusters of students were identified, which differed mainly on the amount of lecture recordings watched, whether the lecture recordings were watched completely or partially, whether the recordings were watched once or multiple times, and the number of lectures the students missed. The five clusters are interpreted as representing different ways of utilising lecture recordings. The clustering provides a basis for investigating the usage of lecture recordings in the context of different approaches to learning and learning strategies.
      PubDate: 2020-01-09
      DOI: 10.25304/rlt.v28.2258
      Issue No: Vol. 28 (2020)
       
 
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