What is Informatics Education Students ' Impression of Using Metacognitive Training System at The First Time?

The use of Metacognitive Training System (MTS) is relatively new in Indonesia. Previously, a prototype of MTS has been developed and applied in Universitas Gadjah Mada. To become a massive product, the prototype of the MTS must be tested on a larger scale. It is intended to capture user impression about a new product. In this paper, we present User Experience (UX) measurement for the developed MTS in larger scale, involving 90 undergraduate students of informatics education at Universitas Negeri Malang. Two UX measurement methods are used, including User Experience Questionnaires (UEQ) and short-interview. UEQ is used for capturing general impressions, whereas, short-interview is conducted to get deeper feedback about the efficacy of the MTS in their studies. The UX measurement result is benchmarked and revealed that Attractiveness, Efficiency, and Stimulation categorized excellent and the interview result shows that more than 75% respondent responds with the positive answer in five questions. With this result, it could be concluded that the MTS is ready for massive product.

[1]  Jun-Ming Su,et al.  A Self-Regulated Learning System to Support Adaptive Scaffolding in Hypermedia-Based Learning Environments , 2014, 2014 7th International Conference on Ubi-Media Computing and Workshops.

[2]  Daniel C. Moos,et al.  Measuring Cognitive and Metacognitive Regulatory Processes During Hypermedia Learning: Issues and Challenges , 2010 .

[3]  Candice Burkett,et al.  Does Training of Cognitive and Metacognitive Regulatory Processes Enhance Learning and Deployment of Processes with Hypermedia? , 2015, CogSci.

[4]  Candice Burkett,et al.  MetaTutor: A MetaCognitive Tool for Enhancing Self-Regulated Learning , 2009, AAAI Fall Symposium: Cognitive and Metacognitive Educational Systems.

[5]  Adhistya Erna Permanasari,et al.  Tahani model of fuzzy database for an adaptive metacognitive scaffolding in Hypermedia Learning Environment (Case: Algorithm and structure data course) , 2017, 2017 International Conference on Sustainable Information Engineering and Technology (SIET).

[6]  Salvador Sánchez Alonso,et al.  Integration of metacognitive skills in the design of learning objects , 2007, Comput. Hum. Behav..

[7]  Mohamed Khaldi,et al.  Metacognitive learning management system supporting self-regulated learning , 2016, 2016 4th IEEE International Colloquium on Information Science and Technology (CiSt).

[8]  Christoph Rensing,et al.  PeerLA - Assistant for Individual Learning Goals and Self-Regulation Competency Improvement in Online Learning Scenarios , 2016, 2016 IEEE 16th International Conference on Advanced Learning Technologies (ICALT).

[9]  Ridi Ferdiana,et al.  Evaluation and measurement of Learning Management System based on user experience , 2016, 2016 6th International Annual Engineering Seminar (InAES).

[10]  Susanne P. Lajoie,et al.  Developing an agent-based adaptive system for scaffolding self-regulated inquiry learning in history education , 2014, Educational Technology Research and Development.

[11]  R. Azevedo Using Hypermedia as a Metacognitive Tool for Enhancing Student Learning? The Role of Self-Regulated Learning , 2005 .