In recent years gaming products have increasingly been used to enhance learning and training development in the academic and commercial sectors.  Gaming is an approach that applies technology to provide an almost real experience with interactive field training.  It is an approach that supports the theory of learning by doing with a real case scenario.  The purpose of this paper is to determine serious game attributes to support effective training using serious game approach.  Through systematic literature review on eleven selected articles, nineteen game attributes were identified.  Hence, based on the definition and description from the articles, text analyses were conducted to determine categories of attributes based on educational theories' perspectives.  This study adopted the deductive content analysis approach which 14 relevant research articles between 1994 and 2016 were identified from the Web of Science and SCOPUS databases.  It appears that serious game attributes according to the educational perspectives are being practised using various ideas, terms and concepts.   Hence, the findings can be justified that serious game attributes are important to enhance the effectiveness of training modules.  All these attributes will become part of the serious game framework for hazard identification training modules.  The target is to deliver effective and active training module to construction-related workers.

<p class="0abstract">Current serious game framework still lacks in fulfilling the user's requirements.  This is due to the framework elements which only focus on the process of delivery.  Hence, this study was carried out to determine user’s ability in self-directed learning and their styles in making a decision.  This study forms part of a larger research on a framework for serious game frameworks for hazard identification training modules.  A set of questionnaire consisting of three sections which are demographic, decision-making styles and levels of self-directed learning was designed.  In decision-making styles, 49 items are measured representing eight styles in decision making such as vigilant, dependent, avoidant, anxious, confident, spontaneous, brooding and intuitive.  Meanwhile, a self-rating scale consisting of 50 items was used to measure the level of self-directed learning such as awareness, learning strategies, learning activities, evaluation and interpersonal skills.  Data was collected from 319 construction-related workers and analysed using mean comparison and ANOVA.  Findings confirmed that their style of decision-making is inclined to ‘vigilant’ and ‘brooding’ types.  The results revealed two levels of self-directed learning, namely, the moderate level for supervisor and high level for general workers, skilled workers, consultants, management teams and safety trainees.  This level of self-directed learning is influenced by their level of education and working experiences.  The findings also highlight that decision-making style has a moderate relationship with the level of self-directed learning among construction-related workers.  The study contributes to the understanding of the construction workers' needs in enhancing their skills in becoming independent and lifelong learners</p>

Augmented reality (AR) has the potential to enhance the teaching and learning experience in construction technology which involves the learning of construction processes and understanding the construction elements. Augmented reality also provides the ability to change and improve the nature of education. This is due to the possibility of overlaying media onto the real world for content consumption using smartphones and tablets devices, which enables students to access information at anywhere and anytime. However, before implementing a new approach to teaching, the state of whether the students are ready to use AR have to be identified. This also goes toward what the students expect when using AR in learning, how do they accept using AR and effectiveness of using AR in learning. Therefore the purpose of this study is to (1) Identify the readiness of students on using AR in teaching; (2) Identifying what do the students expect when using AR in learning construction technology; (3) Identifying the student’s acceptance of AR in learning; (4) The effectiveness of AR in construction technology learning. A quantitative method of analysis has been implemented measuring the mean score of objective 1-3 based on the student’s responses to the questionnaire. On the other hand, the second phase of the study which is to determine whether using AR is effective in learning was done by comparing pre-test and post-test results. Results from the study shows assuring indicators that students accept the usage of AR in construction technology education, the application also fulfils their expectations on what AR could aid in the learning process and for student’s acceptance, the result shows that students accepted the usage of AR as a learning tool. Meanwhile, the results regarding AR effectiveness on construction technology displayed noticeable improvements regarding student’s pre-test and post-test results with 68% of students display improvements in their scores.

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