Analysing the learning pathways of students in a large flipped engineering course

Recent advancements in educational technologies (learning management systems, online discussion forums, peer-learning tools) coupled with new methods of course delivery (e.g. blended, flipped, MOOCs) provide significant opportunities for universities to deliver challenging, high quality, yet engaging curriculum for students. In this paper, we examine the variations and similarities of student's approaches to learning (learning pathways) by examining how well they performed in a large (N ~ 1000 student) first year engineering flipped classroom. The analysis focused on student's performance in their assessment (formative and summative) as well as their online interaction with a range of tools purposely built to support students through peer learning and acquisition of resources and expertise. Analysis using k-means clustering reveals that students do in fact adopt a variety of successful pathways through the course. The unique aspects of this work lie in the use of analytics algorithms that whilst perhaps routinely utilised in data mining, are not as well utilised in better understanding patterns (successful or otherwise) of student interactions within a technology enhanced active learning environment that integrates theory with engineering practice

Understanding Collaboration in Virtual Labs: A Learning Analytics Framework

Online education is increasing and progress within technology has inspired the development of virtual laboratories, which allow students to conduct experiments online. One of the main challenges of virtual laboratory environments is facilitating collaboration similar to those existing in physical laboratory settings. This research explores how one can obtain a better understanding of collaboration in virtual labs through the use of learning analytics. The research work of this thesis was carried out within the frame of design science research, where the main contribution is an artefact in the form of a learning analytics framework. The aim of the artefact is to provide a guiding framework for the integration of learning analytics to better understand and support learning and collaboration in virtual labs. The artefact was evaluated in two iterations using semi-structured interviews with seven experts. It was found through the artefact development process that social network anal- ysis, statistical analysis, natural language processing, and sentiment analysis are valuable data analysis methods for identifying patterns within collaboration in virtual labs. A proposal of a learning analytics dashboard has proved to be a valuable tool to visualise the analysis to the stakeholders in question (students and instructor). The overall reception of the framework was understandable and well-presented. The contribution of this research provides opportunities for future work which involves putting the framework into practice. The implementation of learning analytics to support collaboration in virtual labs can make it easier for students to reflect on their own performances and thereafter improve from it, as well as supporting instructors to reflect on their teaching methods and provide assistance to students in need.Masteroppgave i informasjonsvitenskapINFO390MASV-INF

Using data analytics for collaboration patterns in distributed software team simulations: the role of dashboards in visualizing global software development patterns

This paper discusses how previous work on global software development learning teams is extended with the introduction of data analytics. The work is based on several years of studying student teams working in distributed software team simulations. The scope of this paper is twofold. First it demonstrates how data analytics can be used for the analysis of collaboration between members of distributed software teams. Second it describes the development of a dashboard to be used for the visualization of various types of information in relation to Global Software Development (GSD). Due to the nature of this work, and the need for continuous pilot studies, simulations of distributed software teams have been created with the participation of learners from a number of institutions. This paper discusses two pilot studies with the participation of six institutions from two different countries

Using data analytics for collaboration patterns in distributed software team simulations: the role of dashboards in visualizing global software development patterns

This paper discusses how previous work on global software development learning teams is extended with the introduction of data analytics. The work is based on several years of studying student teams working in distributed software team simulations. The scope of this paper is twofold. First it demonstrates how data analytics can be used for the analysis of collaboration between members of distributed software teams. Second it describes the development of a dashboard to be used for the visualization of various types of information in relation to Global Software Development (GSD). Due to the nature of this work, and the need for continuous pilot studies, simulations of distributed software teams have been created with the participation of learners from a number of institutions. This paper discusses two pilot studies with the participation of six institutions from two different countries

Elearning, Communication and Open-data: Massive Mobile, Ubiquitous and Open Learning

ABSTRACT: In MOOCs, learning analytics have to be addressed to the various types of learners that participate. This deliverable describes indicators that enable both teachers and learner to monitor the progress and performance as well as identify whether there are learners at risk of dropping out. How these indicators should be computed and displayed to end users by means of dashboards is also explained. Furthermore a proposal based on xAPI statements for storing relevant data and events is provided

ECO D2.5 Learning analytics requirements and metrics report

In MOOCs, learning analytics have to be addressed to the various types of learners that participate. This deliverable describes indicators that enable both teachers and learner to monitor the progress and performance as well as identify whether there are learners at risk of dropping out. How these indicators should be computed and displayed to end users by means of dashboards is also explained. Furthermore a proposal based on xAPI statements for storing relevant data and events is provided.Part of the work carried out has been funded with support from the European Commission, under the ICT Policy Support Programme, as part of the Competitiveness and Innovation Framework Programme (CIP) in the ECO project under grant agreement n° 21127

Investigating the role of biometrics in education – the use of sensor data in collaborative learning

This paper provides a detailed description of how a smart spaces laboratory has been used for assessing learners’ performance in various educational contexts. The paper shares the authors’ experiences from using sensor-generated data in a number of learning scenarios. In particular the paper describes how a smart learning environment is created with the use of a range of sensors measuring key data from individual learners including (i) heartbeat, (ii) emotion detection, (iii) sweat levels, (iv) voice fluctuations and (v) duration and pattern of contribution via voice recognition. The paper also explains how biometrics are used to assess learner’ contribution in certain activities but also to evaluate collaborative learning in student groups. Finally the paper instigates research in the role of using visualization of biometrics as a medium for supporting assessment, facilitating learning processes and enhancing learning experiences. Examples of how learning analytics are created based on biometrics are also provided, resulting from a number of pilot studies that have taken place over the past couple of years

Design guideline for UTM academician personal research and publication dashboard

The dashboard displayed the organization’s important information on a single screen which enables them to monitor their performance and make necessary decisions. However, the biggest issue that a dashboard has is it does not have specific design guideline for the developer to follow. Addressing this issue, this study is executed to find a suitable dashboard design guideline and use it to design a dashboard for the academicians from Universiti Teknologi Malaysia (UTM). The purpose of this study is to identify dashboard design guideline for UTM APRPD, visualization features to be included in the UTM APRPD, and to validate the dashboard design guideline identified. UTM Academician Personal Research and Publication Dashboard (UTM APRPD) is a dashboard designed to monitor and analyze UTM academician’s individual performance in publication and research grant performance. This study is using the Research and Development Information System (RADIS) as its case study. The dashboard design guideline used to design the UTM APRPD was validated by analyzing the result obtained from the interview session with the respondents. In contrast to the RADIS, UTM APRPD interface design was improved to visually aid the academicians in monitoring their performance. The academicians agree that the dashboard was designed fine and are relevant to be used. Thus, the dashboard design guidelines identified in this study can be used to design the UTM APRPD

User-Centred Design for team mood: The design of a digital dashboard.

Work environments are becoming increasingly collaborative, but team management applications typically lack features that focus on the team mood and employees' emotions. The purpose of this thesis is to design a tool that helps employees share their feelings and team managers create a positive work environment. Current market analysis and emotion theories were identified during an ideation phase. A user-centred design method is used to gather contextual data about the needs of employees at Philips, a large health technology company, design prototypes of a team dashboard for emotions and conduct two user studies to evaluate the prototypes. Interview and survey results were analysed to find that study participants preferred moving images rather than text to select emotions, were generally favourable toward inputting emotions and had various suggestions about privacy, the importance of face-to-face meetings and new features. This thesis describes the motivations behind the project, the design of a unique team management solution and potential benefits and advantages of a final system

Do You Know What I Know?:Situational Awareness of Co-located Teams in Multidisplay Environments

Modern collaborative environments often provide an overwhelming amount of visual information on multiple displays. In complex project settings, the amount of visual information on multiple displays, and the multitude of personal and shared interaction devices in these environments can reduce the awareness of team members on ongoing activities, the understanding of shared visualisations, and the awareness of who is in control of shared artifacts. Research reported in this thesis addresses the situational awareness (SA) support of co-located teams working on team projects in multidisplay environments. Situational awareness becomes even more critical when the content of multiple displays changes rapidly, and when these provide large amounts of information. This work aims at getting insights into design and evaluation of shared display visualisations that afford situational awareness and group decision making. This thesis reports the results of three empirical user studies in three different domains: life science experimentation, decision making in brainstorming teams, and agile software development. The first and the second user studies evaluate the impact of the Highlighting-on-Demand and the Chain-of-Thoughts SA on the group decision-making and awareness. The third user study presents the design and evaluation of a shared awareness display for software teams. Providing supportive visualisations on a shared large display, we aimed at reducing the distraction from the primary task, enhancing the group decision-making process and the perceived task performance