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<p>Problem framing is an essential stage in engineering design mainly because it is crucial in developing solutions to design problems. Engineers’ ability to frame a problem is naturally attributed to their reasoning abilities and expertise. Traditionally, our understanding of the type of reasoning is originated from cognitive sciences, sociology, and psychological theories of reasoning. Design reasoning models developed from these disciplines contributed significantly to understanding design reasoning. However, a different standpoint for understanding specialized form of knowledge and reasoning that are unique to engineering practices is needed.</p> <p>An important contribution of this dissertation to the body of research is its use of a new theoretical model, Design Reasoning Quadrants, developed to help organize types of design reasoning at the intersection of two axes, the disciplinary-multidisciplinary reasoning axis and theoretical-practical reasoning axis. Further, this dissertation uses the Design Reasoning Quadrants framework to understand first-year engineering students' reasoning while framing design problems. Prior research stated that it is necessary to elicit the forms of reasoning beginner students have while dealing with design problems, to improve problem-solving abilities. Therefore, this dissertation addresses the need to understand first-year engineering students' reasoning, while engaging in problem framing using four design reasoning quadrants: experiential observations, first principles, trade-offs, and complex abstractions.</p> <p>This dissertation examined changes in first-year engineering students’ design reasoning during problem framing across two different design projects students explored within a semester in an engineering course. The main data sources were answers to a questionnaire students completed in the first and final design project as the first-in-lecture activity for problem framing. Students answered each questionnaire individually. The analysis took place in two stages. </p> <p>First, a deductive analysis was conducted to identify types of reasoning in students’ formulated questions to understand a problem. Using a multinomial logit model and descriptive statistics, differences in the theoretical-practical and disciplinary-multidisciplinary reasoning through the time were identified. Second, students’ answers to the design reasoning quadrants’ questions were analyzed deductively and inductively. This analysis aimed to identify students’ design reasoning patterns when elicited in one of the four design reasoning quadrants.</p> <p>The results of the deductive analysis indicated that regardless of the design project, student reasoning in terms of the theoretical-practical reasoning is not significantly different between the two time points. However, students’ reasoning was more heavily disciplinary-focused in the second project and more multidisciplinary in the first design project. The results of the inductive analysis helped further explain this result. This analysis revealed that students were more familiar with the context and disciplinary concepts for the first rather than for the second design project.</p> <p>The results of this dissertation and framework can help researchers further understand how students reason from the perspective of the nature of engineering. In addition, understanding the type of reasoning students use while framing a problem will allow educators to understand the reasoning beginner students employ while framing a problem and to develop better learning experiences to enhance problem-solving skills.</p>

Good academic literacy skills are vital for success in the 21st century for students in higher education and for professional people in the workforce to be able to process and convey information and knowledge. The purpose of the current study was to gain insights into the construct of academic literacy skills and to identify indicators affecting the development of the academic literacy skills of first year students in higher education. To this end, a case study was done on a cohort of 20 first year male Emirati students attending an academic literacy skills course in an engineering higher education institute in the Arabian Gulf region. The study was guided by three research questions concerning the development of academic literacy skills which were defined as writing strategies, library research strategies and general study skills (Bury, Sheese & Katz, 2013). Data gathered comprised surveys, grade comparisons, written assignments, semi-structured interviews, classroom observations recorded using a video camera and instructor observations. The framework of Academic Literacies developed by Lea and Street (1998, 2000, 2006) was used for analysis with a focus on the supplementing constructs of study skills and academic socialization. To extract more detailed knowledge and further insights about the students’ academic literacy skills, a comparison was also made between the developmental indicators regarding successful and non-successful students’ written work and their approaches to completing assignments. The indicators revealed included the students’ lack of library research strategies, digital literacy skills and sense of ownership. Theoretical and practical implications for developing students’ academic literacy skills are provided in conclusion.

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Basic mathematical competency seems to be lacking for engineering students starting their studies in this field. Students generally find the cognitive transition from secondary to tertiary mathematics challenging which in turn negatively influences their academic achievement in mathematics. The cognitive challenge is the transition from the application of mathematics to familiar questions to applying mathematical principles to varying practical application and problem solving. Mathematics provides the foundation for the cognitive toolset required for the development of skills required for analysing engineering systems and processes. It is therefore important to assess mathematical and cognitive competency and ability at the time of admission to a tertiary institution in order to identify and address gaps. This research demonstrates that first-year engineering students need to have a specific level of mathematical competency and cognitive ability to use mathematics within the context of engineering studies. This research attempts to connect the mathematic competency of first year engineering students to their academic results for subjects in the first year curriculum that rely heavily on mathematical competency. To satisfy the research question, the study firstly looks at relevant literature to identify the mathematical competency levels as well as the operational specification. Secondly, development theories and taxonomies were analysed to gain insight into the development processes associated with learning, cognitive development and the gap between cognitive competencies in transition from secondary to tertiary education. Further, cognitive competencies were identified that are essential for successful completion of first year engineering modules. Through synthesis of the different theories and taxonomies a framework was identified. This framework was used to analyse secondary data in order to measure mathematical and cognitive levels. Thirdly, the theoretical investigation was followed by a three-phase empirical study. A mixed quantative-qualitative (QUAN-qual) approached was followed. Phase 1 uses the assessment framework to measure first year students‟ mathematical competency at the inception of their studies as well as at the completion of their first semester. The mathematical competency at inception was measured with their Grade 12 mathematics marks and with relevant analysis of their initial bridging assessments, on a question by question basis. In addition, their first semester exams questions were analysed using the same approach as above. Phase 2 comprises the measurement of the relationship between the mathematical competency of first year enigineering students at admission and their achievement levels in selected first year subjects that required mathematical competency. Phase 3 includes the guidelines derived from the gaps and shortcomings identified. These gaps were identified in order to inform appropriate study support to first year students and to assists academic personnel with setting appropriate and dependable admission standards. The analysis of mathematical competency creates quality data that gives a clearer picture than a simple comparison of admission scores and first semester marks. The empirical study contributes to a better understanding of the problems associated with the transition from secondary to tertiary learning environments. From the study it was derived that study inception information of the students correlated only with their academic results on questions that tested mathematical and programming application. The inception information was not a predictor of mathematical achievement and results for both the lowest and highest mathematical competency levels. Futher study in this field is required to create frameworks for the measurements of both low and high levels of mathematical competency. / MEd (Mathematics Education), North-West University, Potchefstroom Campus, 2014

Basic mathematical competency seems to be lacking for engineering students starting their studies in this field. Students generally find the cognitive transition from secondary to tertiary mathematics challenging which in turn negatively influences their academic achievement in mathematics. The cognitive challenge is the transition from the application of mathematics to familiar questions to applying mathematical principles to varying practical application and problem solving. Mathematics provides the foundation for the cognitive toolset required for the development of skills required for analysing engineering systems and processes. It is therefore important to assess mathematical and cognitive competency and ability at the time of admission to a tertiary institution in order to identify and address gaps. This research demonstrates that first-year engineering students need to have a specific level of mathematical competency and cognitive ability to use mathematics within the context of engineering studies. This research attempts to connect the mathematic competency of first year engineering students to their academic results for subjects in the first year curriculum that rely heavily on mathematical competency. To satisfy the research question, the study firstly looks at relevant literature to identify the mathematical competency levels as well as the operational specification. Secondly, development theories and taxonomies were analysed to gain insight into the development processes associated with learning, cognitive development and the gap between cognitive competencies in transition from secondary to tertiary education. Further, cognitive competencies were identified that are essential for successful completion of first year engineering modules. Through synthesis of the different theories and taxonomies a framework was identified. This framework was used to analyse secondary data in order to measure mathematical and cognitive levels. Thirdly, the theoretical investigation was followed by a three-phase empirical study. A mixed quantative-qualitative (QUAN-qual) approached was followed. Phase 1 uses the assessment framework to measure first year students‟ mathematical competency at the inception of their studies as well as at the completion of their first semester. The mathematical competency at inception was measured with their Grade 12 mathematics marks and with relevant analysis of their initial bridging assessments, on a question by question basis. In addition, their first semester exams questions were analysed using the same approach as above. Phase 2 comprises the measurement of the relationship between the mathematical competency of first year enigineering students at admission and their achievement levels in selected first year subjects that required mathematical competency. Phase 3 includes the guidelines derived from the gaps and shortcomings identified. These gaps were identified in order to inform appropriate study support to first year students and to assists academic personnel with setting appropriate and dependable admission standards. The analysis of mathematical competency creates quality data that gives a clearer picture than a simple comparison of admission scores and first semester marks. The empirical study contributes to a better understanding of the problems associated with the transition from secondary to tertiary learning environments. From the study it was derived that study inception information of the students correlated only with their academic results on questions that tested mathematical and programming application. The inception information was not a predictor of mathematical achievement and results for both the lowest and highest mathematical competency levels. Futher study in this field is required to create frameworks for the measurements of both low and high levels of mathematical competency. / MEd (Mathematics Education), North-West University, Potchefstroom Campus, 2014