How Peripheral Data Visualisation Systems Support Secondary School Teachers during VLE-Supported Lessons

Through the integration of technology-enhanced learning (TEL) in the classrooms, there is an increase in Virtual Learning Environment-supported classes in secondary schools, which brings unintentional complexities in terms of monitoring for teachers [25]. To support secondary school teachers during VLE-supported lessons, a peripheral data visualisation system was designed and implemented in a three-week field study. Both qualitative and quantitative data were gathered and analysed through methodological triangulation in order to get an in-depth understanding about the use of the system by teachers. The key findings from our study were that the peripheral data visualisation tool, by being a distributed, highly visible system, was well integrated in the teachers' practice. The peripheral visualisation served as a trigger for teacher interventions where the teacher could confront the student's level of concentration and provide support when a student needs it. Furthermore, by offloading the secondary tasks of checking the students' level of concentration and progress to the visualisation, most teachers experienced more peace of mind and space to manage their primary teaching practice. Lastly, approximately 95% of 89 students experienced the data visualisation as neutral or motivating, while 5.7% of the students experienced violation of privacy by this medium.

[1]  John Seely Brown,et al.  The coming age of calm technolgy , 1997 .

[2]  R. Heale,et al.  Understanding triangulation in research , 2013, Evidence-Based Nursing.

[3]  Larry Cuban,et al.  High Access and Low Use of Technologies in High School Classrooms: Explaining an Apparent Paradox , 2001 .

[4]  Erik Duval,et al.  Learning dashboards: an overview and future research opportunities , 2013, Personal and Ubiquitous Computing.

[5]  Vincent Aleven,et al.  Intelligent tutors as teachers' aides: exploring teacher needs for real-time analytics in blended classrooms , 2017, LAK.

[6]  K. Ryon Descriptive and Inferential Statistics , 2013 .

[7]  Martijn H. Vastenburg,et al.  Designing to Support Social Connectedness: The Case of SnowGlobe , 2011 .

[8]  Pierre Dillenbourg,et al.  An Ambient Awareness Tool for Supporting Supervised Collaborative Problem Solving , 2012, IEEE Transactions on Learning Technologies.

[9]  Göran Brante,et al.  Multitasking and synchronous work: Complexities in teacher work , 2009 .

[10]  Saskia Bakker Design for peripheral interaction , 2013 .

[11]  Berry Eggen,et al.  Understanding teachers’ routines to inform classroom technology design , 2016, Education and Information Technologies.

[12]  María Jesús Rodríguez-Triana,et al.  Monitoring, Awareness and Reflection in Blended Technology Enhanced Learning: a Systematic Review , 2017 .

[13]  Pierre Dillenbourg,et al.  Teaching analytics: towards automatic extraction of orchestration graphs using wearable sensors , 2016, LAK.

[14]  María Jesús Rodríguez-Triana,et al.  Contextual learning analytics apps to create awareness in blended inquiry learning , 2015, 2015 International Conference on Information Technology Based Higher Education and Training (ITHET).

[15]  Saskia Bakker,et al.  Lernanto: Using an Ambient Display During Differentiated Instruction , 2016, CHI Extended Abstracts.

[16]  Berry Eggen,et al.  FireFlies2: Interactive Tangible Pixels to enable Distributed Cognition in Classroom Technologies , 2017, ISS.

[17]  Carlos Delgado Kloos,et al.  GLASS: a learning analytics visualization tool , 2012, LAK '12.

[18]  Ehsanollah Habibi,et al.  Evaluation of Rating Scale Mental Effort (RSME) effectiveness for mental workload assessment in nurses , 2016 .

[19]  S. Kuhar,et al.  Taking Advantage of Education Data: Advanced Data Analysis and Reporting in Virtual Learning Environments , 2011 .

[20]  Miguel Ángel Conde González,et al.  Can we predict success from log data in VLEs? Classification of interactions for learning analytics and their relation with performance in VLE-supported F2F and online learning , 2014, Comput. Hum. Behav..

[21]  V. Braun,et al.  Using thematic analysis in psychology , 2006 .

[22]  Elise van den Hoven,et al.  Peripheral interaction: characteristics and considerations , 2014, Personal and Ubiquitous Computing.

[23]  Stephen Adams,et al.  Using a large display in the periphery to support children learning through design , 2011, IDC.

[24]  Peter J. Denning,et al.  Beyond calculation - the next fifty years of computing , 1997 .

[25]  Elise van den Hoven,et al.  FireFlies: physical peripheral interaction design for the everyday routine of primary school teachers , 2013, TEI '13.

[26]  Patrick Jermann,et al.  Classroom orchestration: The third circle of usability , 2011, CSCL.

[27]  Tara Matthews,et al.  A toolkit for managing user attention in peripheral displays , 2004, UIST '04.

[28]  Erik Duval,et al.  The student activity meter for awareness and self-reflection , 2012, CHI Extended Abstracts.

[29]  Berry Eggen,et al.  ClassBeacons: Designing Distributed Visualization of Teachers' Physical Proximity in the Classroom , 2018, TEI.

[30]  Panos Markopoulos A Design Framework for Awareness Systems , 2009, Awareness Systems.