Tag Archives: awareness

Type: Evidence | Proposition: A: Learning | Polarity: | Sector: | Country:

This literature paper briefly anticipates and outlines a project about integrating labour market information in a learning analytics goal-setting application, with the aim to help student to develop skills that are currently requested by the labour market.

Authors highlight the absurd contemporary trend that characterise labour market, with high levels of youth unemployment together with difficulties of companies to find candidates with the right job skills.

In the developed IT solution, abour market data will be analyzed to extract information that may impact student planning. This will lead to a "goal-setting program in which students can specify goals (e.g., learning goals as subgoals of more distant career goals)" and have access to "relevant labour market information, view progress and success indicators, and receive recommendations from course advisors".

According to authors, "this research expands the impact of learning analytics beyond the educational setting by helping students to navigate the education-to-employment pathway using a goal-setting application" characterized by analytical methods joint with an examination of learning constructs and educational theories.

Citation: V. Kobayashi, S.T. Mol, G. Kismihók (2014). Labour Market Driven Learning Analytics. Journal of Learning Analytics, 1(3), 207-210 | Url: https://epress.lib.uts.edu.au/journals/index.php/JLA/article/view/4194

Type: Evidence | Proposition: A: Learning | Polarity: | Sector: | Country:

In recent years, one of the main issues for companies in hiring new employees consists in the bridge between skills provided by HE and the ones required by a more and more fast and agile market. This is why it is particular important for students to identify as soon as possible what can be their career fields, taking into consideration natural attitudes and personal wishes.

In this scientific paper, authors describe the development of a tool, or a Portal, to improve career readiness of students during Higher Education. IT tools like this are particularly interesting, because gives to companies the potential capability to have visibility on the areas of interests of the best graduates, and contacting them soon as they finish their studies, as well as compare these attitudes with workplace results and skill improvements.

This Portal consists of three major processes:

1) Career Readiness

2) Career Prediction

3) Career Development.

Career Readiness is formed  by different software modules which allows to measure the general professional dispositions required for a successful career in the 21st Century (21st Century Skills). These professional dispositions have been divided in 6 macro-areas, which in general describe  "the natural tendencies, mind state and preparations of each individual towards a professional practice": Openness to challenge, Critical Thinking, Resilience, Learning Relationships, Responsibility for Learning, and Creativity.

Career Prediction is calculated on some indicators, which are transformed in "Raw scores", that allows to cluster individuals and compare them with the features of different Community of Practice (people who share knowledge, experiences and passion on the same set of topics).

Career Development, which allows people to join different Communities of Practice and build their career domain awareness and skills.

The  tool integrates Learning Analytics techniques for career readiness "by focusing on meta-learning dimensions that accompany formal education while positioning learners and instructors at the center of the analytics process". Learning Analytics allows to provide solutions to help learners to reflect and act upon feedback about their learning performance.  Furthermore, Learning Analytics reveals hidden patterns of common traits among learners viewed as future candidates of the job market.

Citation: AbuKhousa, E.; Atif, Y., "Big learning data analytics support for engineering career readiness," in Interactive Collaborative Learning (ICL), 2014 International Conference on , vol., no., pp.663-668, 3-6 Dec. 2014 doi: 10.1109/ICL.2014.7017849 | Url: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=7017849&punumber%3D7002490%26sortType%3Dasc_p_Sequence%26filter%3DAND(p_IS_Number%3A7017737)%26pageNumber%3D4

Type: Evidence | Proposition: A: Learning | Polarity: | Sector: | Country:

This longitudinal study explores the effects of tracking and monitoring time devoted to learn with a mobile tool, on self-regulated learning. Graduate students (n = 36) from three different online courses used their own mobile devices to track how much time they devoted to learn over a period of four months. Repeated measures of the Online Self-Regulated Learning Questionnaire and Validity and Reliability of Time Management Questionnaire were taken along the course. Our findings reveal positive effects of tracking time on time management skills. Variations in the channel, content and timing of the mobile notifications to foster reflective practice are investigated, and time-logging patterns are described. These results not only provide evidence of the benefits of recording learning time, but also suggest relevant cues on how mobile notifications should be designed and prompted towards self-regulated learning of students in online courses.

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Citation: Tabuenca, B., Kalz, M., Drachsler, H., & Specht, M. (2015). Time will tell: The role of mobile learning analytics in self-regulated learning. Computers & Education, 89, 53–74. | Url: http://dspace.ou.nl/handle/1820/6172

Type: Evidence | Proposition: B: Teaching | Polarity: | Sector: | Country:

SAM (Student Activity Meter) visualizes time spent on learning activities and resource use in online learning environments.

Teacher goals. SAM provides support for the following teacher objectives:

  • Awareness for teachers of what and how learners are doing is important to assess learner progress. This is difficult in online and distant courses due to lack of face-to-face communication. SAM provides visual overviews of the time learners spent and the resources they use. Both are good indicators for awareness. The visualizations can be used by teachers to find patterns and spot potential problems.
  • Time tracking  information allows teachers to assess their initial time estimates with the real time spending of students and find the exercises that consume most time.
  • The resource usage  can show the popular learning materials and enables resource discovery, through a list of most used or most time spent on resources in SAM.


Table of the Likert scale analysis of the teaching issues and the issues addressed by the tool (IQR=InterQuartile Range):

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Table of the Likert scale analysis of usefulness of the visualizations of the CGIAR case study (IQR=InterQuartile Range):

Table of the Likert scale analysis of usefulness of the visualizations of the CGIAR case study (IQR=InterQuartile Range)

The CGIAR case study shows that SAM contributes to creating awareness for teachers, as evidenced by the survey results. SAM meets the time tracking goal. The resource use can be improved by differentiating internal and online resources. Overall, teachers would like more statistics. SAM’s three visualizations were perceived as useful in the CGIAR case and 18 out of 20 teachers would like to use SAM in their own courses. This confirms that SAM provides useful functionality for teachers.


Citation: S. Govaerts, K. Verbert, and E. Duval. Evaluating the student activity meter: Two case studies. In H. Leung, E. Popescu, Y. Cao, R. Lau, and W. Nejdl, editors, Advances in Web-Based Learning - ICWL 2011, volume 7048 of Lecture Notes in Computer Science, pages 188-197. Springer Berlin Heidelberg, 2011. | Url: http://link.springer.com/chapter/10.1007%2F978-3-642-25813-8_20