Connecting Incoming Freshmen With Engineering Through Hands-On Projects

Engineering programs suffer a high attrition rate, which causes the nation to graduate much less engineers. A survey of the literature reveals that the high attrition rate is due mainly to the fact that the first year of an engineering program is all fundamental theory and students don't see the connection to their future engineering careers. To address this problem, educators in the Roy G. Perry College of Engineering at Prairie View A&M University launched a five-week summer camp entitled “College of Engineering Enhancement Institute (CE2I)” aimed at improving the performance of incoming freshmen in mathematics by one level and a smoother transition between high school and college. Each department in the college participated by introducing their individual curriculum through hands-on projects designed by faculty members. Computer Engineering, Computer Science and Computer Engineering Technology programs implemented multimedia projects to tie the incoming freshman to their selected majors. Results show that the camp met the expectations and successfully points the directions for our future engineering education practices.

The Impact of Computer Augmented Online Learning and Assessment

The purpose of the study was to investigate the impact of an experimental online learning tool on student performance. By applying cognitive load theory to online learning, the experimental tool used was designed to minimize cognitive load during the instructional and learning process. This tool enabled students to work with programming code that was supplemented with instructor descriptions and feedback, embedded directly within the code while maintaining the original integrity of the coding environment. A sample of 24 online graduate students at a southeastern university were randomly assigned to four groups: Group 1 (Control group), Group 2 (Assessment group: the tool was used to provide feedback on student work), Group 3 (Lecture group: the tool was used to describe examples of code provided in lectures), and Group 4 (Total tool group: the tool was used to provide feedback on student work as well as describe examples of code in lectures). Student learning was measured via analysis of six online quizzes. While provision of tool-facilitated feedback alone did not appear to enhance student learning, the results indicate that students performed best when they had the opportunity to view examples of code facilitated by the tool during the learning process of new material. This implies a carefully designed online learning environment, especially while controlling for and minimizing cognitive load when presenting new information, can enhance that student learning

Natural Language Tutoring and the Novice Programmer

For beginning programmers, inadequate problem solving and planning skills are among the most salient of their weaknesses. Novices, by definition, lack much of the tacit knowledge that underlies effective programming. This dissertation examines the efficacy of natural language tutoring (NLT) to foster acquisition of this tacit knowledge. Coached Program Planning (CPP) is proposed as a solution to the problem of teaching the tacit knowledge of programming. The general aim is to cultivate the development of such knowledge by eliciting and scaffolding the problem solving and planning activities that novices are known to underestimate or bypass altogether. ProPL (pro-PELL), a dialogue-based intelligent tutoring system based on CPP, is also described. In an evaluation, the primary findings were that students who received tutoring from ProPL seemed to exhibit an improved ability compose plans and displayed behaviors suggestive of thinking at greater levels of abstraction than students in a read-only control group. The major finding is that NLT appears to be effective in teaching program composition skills

Teaching and learning introductory programming : a model-based approach

The dissertation identifies and discusses impact of a model-based approach to teaching and learning introductory object-oriented programming both for practitioners and for computer science education research.Learning to program is notoriously difficult. This dissertation investigates ways to teach introductory object-oriented programming at the university level. It focuses on a model-based approach, describes and argues for this approach and investigates several of its aspects. It gives an overview of the research in teaching introductory programming in an objects-first way. The dissertation also investigates ways for university teachers to share and document best practices in teaching introductory object-oriented programming through pedagogical patterns. The dissertation addresses both traditional young full-time students and experienced programmers (although not in object-orientation) participating in part-time education. It examines whether the same success factors for learning programming apply to a model-based approach as to introductory programming courses in general for full-time students and gives a general overview of research in success factors for introductory programming. Some factors are the same, because students‘ math competence is positively correlated with their success. The dissertation examines how experienced programmers link a model-based programming course to their professional practices. The general answer is that the part-time students do not need to have a direct link to their specific work-practice, they expect to create the link themselves; but the teacher must be aware of the conditions facing the part-time students in industry. Furthermore, the dissertation addresses interaction patterns for part-time students learning model-based introductory programming in a net-based environment. A previously prepared solution to an exercise is found to mediate the interaction in three different ways. Design patterns have had a major impact on the quality of object-oriented software. Inspired by this, researchers have suggested pedagogical patterns for sharing best practices in teaching introductory object-oriented programming. It was expected that university teachers‘ knowledge of pedagogical patterns was limited, but this research proved that to be wrong; about half of the teachers know pedagogical patterns. One of the problems this dissertation identifies is the lack of a structuring principle for pedagogical patterns; potential users have problems identifying the correct patterns to apply. An alternative structuring principle based on a constructivist learning theory is suggested and analysed

Challenges of teaching and studying programming at a university of technology - Viewpoints of students, teachers and the university

This thesis analyses the challenges of the instructional process at a university of technology from the viewpoints of students, teachers and the university administration. The first research question concerns the difficulties students encounter when they study computer programming. Special attention was given to the students' reasons for dropping out of the introductory programming course (CS1). The second research question concerns computer science teachers' conceptions of studying and teaching. The third research question concerns how the instructional process was seen at the teaching organisation level. These three viewpoints represent holistic approach to the challenges of the instructional process. General System Theory (GST) was used as the framework throughout the theoretical and empirical parts of this thesis. Three analysis models were developed: the "dimension doughnut", the three-layered didactic triangle and the feedback loop. These tools were used as starting points for developing the categorisation of earlier literature based on its didactic focus, and to analyse systematically the collected empirical data. The empirical data was collected from students in the introductory programming course, computer science teachers, representatives of the administration and formal documents. Both qualitative and quantitative research methods were utilised. The results suggest that the students' reasons for dropping out of the CS1 course were manifold and that they tend to cumulate. On average, dropped out students reported ten reasons that contributed to their decision, of which four affected their decision critically. The reasons included: course arrangements, difficulties to understand course topics, difficulties with time management, no consequences for dropping out, and preference for other courses. Computer science teachers' conceptions of studying were often content oriented. The teachers considered theory and concepts of computer science and the ability to apply knowledge to be the most difficult for the students. The experiences from the previous years courses and customs affected greatly the teaching process. Due to the large-scale courses, it was difficult to make adjustments to the ongoing course. The analysis of the formal documents and interview data of the administrative personnel revealed problematic aspects. For example, goal setting and planning were substance oriented. As a result, soft skills were not systematically discussed or taught during the studies. Moreover, the collection of feedback was not systematic and collected feedback was not always utilised. The results highlighted how students', teachers' and organisation's instructional processes interrelated