Nguyen, Trang Thi Thuy (2015) Mental models of first-year education students studying information communication technologies. PhD thesis, James Cook University.

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Abstract

The attrition of first-year university students is an important political, socioeconomic, educational, and community issue. Surmounting the intellectual challenges associated with transition problems to university, especially in the first six months, is crucial for developing appropriate academic learning habits and strategies. This doctoral thesis investigates mental models of first-year students undertaking a Bachelor of Education degree and how these might be related to their learning practices.

Mental models have been described as an internal, domain-specific representation of an object, system, or event that may be incomplete. Through their mental models, individuals are able to understand and explain the unknown and, with regard to problems, decide what course to follow, and predict consequences. Mental models are successful tools for the acquisition of knowledge, understanding, and problem-solving strategies in order to make such skills available in different situations. Mental models are seen as an important key to students' knowledge, critical thinking skills, and problem solving in learning environments. Mental models are also seen as predictive tools to students' learning performance and results.

The aim of this research was to build a picture of students' mental models in their first semester of first-year using one subject (course) as the context. In particular, the research questions asked were as follows: (1) What are students' mental models of themselves as first-year university students at the beginning and at the end of the subject? (2) What major changes, if any, occurred in the students' mental models across a semester period? and (3) Which mental models, if any, relate to students' learning achievement?

The sample comprised 102 first-year Bachelor of Education volunteer students studying the core first-year subject, Information and Communication Technologies in Education, in a regional university in Australia. This thesis employed a mixed-method approach but primarily used quantitative methodology. The data collection tools comprised Likert-scale questionnaires which drew on well-established research about student learning and open-ended questions administered as pre- and post-surveys.

There were 50 items in each questionnaire based on questionnaire items in the research literature and they were categorised into seven mental model subscales. The seven mental models were: (1) the Sense of Purpose and Expectation Mental Model, (2) the Motivation Mental Model, (3) the Learning Strategy Mental Model, (4) the Collaboration Mental Model, (5) the Poor Coping and Comprehension Mental Model, (6) the Un-motivation and Ineffective Learning Strategy Mental Model, and (7) the Poorly Prepared and Absent Mental Model.

Statistical tests used to identify mental models of students included exploratory factor analysis, correlations analysis, paired sample t-tests, independent sample t-tests, one-way analyses of variance (ANOVA), and stepwise multiple regression analyses. Qualitative data obtained from the open-ended questions was thematically coded and the results were compared with the findings of the statistical analysis.

The five mental models that were identified at the beginning of the subject from the exploratory factor analysis were: (1) the Motivation, Goal, and Academic Engagement Mental Model, (2) the Coping and Expectation Mental Model, (3) the Collaboration Mental Model, (4) the Learning Strategy Mental Model, and (5) the Unmotivation Mental Model. The sample size in this study (102 students) was just within the acceptable range (100) and the Kaiser-Myer Olkin measure of sampling adequacy at pre-test was acceptable. However, the reliability analysis revealed that the Coping and Expectation Mental Model was unusable and the reliability coefficients of four other mental models were modest to acceptable. Therefore a second exploratory factor analysis on the post-test was not performed. To measure changes in the students' mental models at pre-test and post-test in the quantitative data, the seven mental model subscales were used. Three mental models were found in the qualitative data in both at the beginning at the end of semester one: the Difficulty in Coping and Comprehension Mental Model, the Academic Engagement Mental Model, and the Weak Academic Expectation Mental Model. The results of the quantitative and qualitative data analysis were discussed together to investigate students' mental models of learning.

This research determined that by the end of the semester, students' mental models of learning were difficult to change. Either they had not changed or if they had, the changes were generally not indicative of better mental models of learning. Also, differences were found in the mental models of students by gender and school completion time (school leaver/mature age students). Furthermore, there was a relationship between students' mental models and their learning achievement. The results determined that only the Poorly Prepared and Absent Mental Model of students at pre-test was a predictor of the academic grades of students. This mental model negatively impacted student learning achievement.

The findings of the study have implications for university practice. Implementing a program during the semester that helps students to recognise any weaknesses in their mental models of learning is a recommendation. There should be an emphasis on such programs not simply in terms of increasing skills acquisition but in terms of a program which might target students' mental models of learning. For lecturers of subjects that involve information communication technologies, the interventions such as better instructional design could help students to develop their mental models. Effective instruction can motivate and engage students to learn more and retain new knowledge in their long-term memory which enables them to incorporate and organise new information into more complete mental models.

This thesis has contributed to the mental models research of the first-year university experience in particular of pre-service teachers. Future research is needed to further examine mental models with larger groups of students and particularly, to investigate changes in students' mental models not only in the first semester, but also in the second semester of the first-year and possibly in the following years. Further studies of students in other disciplines, especially where a range of ICT tools are used as learning tools, will enable a comparison of results to help produce a clearer picture of the mental models of first-year university students.

Item ID:	49402
Item Type:	Thesis (PhD)
Keywords:	academic engagement, cognitive overload, collaboration, college students, disengagement, effective learning strategy, factor analysis, first year education students, ineffective learning strategy, learning strategies, mental models, pre-service teacher education, retention, working memory
Date Deposited:	16 Jun 2017 00:21
FoR Codes:	17 PSYCHOLOGY AND COGNITIVE SCIENCES > 1701 Psychology > 170103 Educational Psychology @ 30% 13 EDUCATION > 1301 Education Systems > 130103 Higher Education @ 70%
SEO Codes:	93 EDUCATION AND TRAINING > 9301 Learner and Learning > 930101 Learner and Learning Achievement @ 50% 93 EDUCATION AND TRAINING > 9301 Learner and Learning > 930102 Learner and Learning Processes @ 50%
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