Success and Learning Style Alignment in Introductory Business Computing

In this paper, three-year study conducted with first year undergraduate business computing students enrolled at a New Zealand higher education institution is considered. Results suggest that there is an educational challenge in higher education at entry level. One hundred and eighty five students from seven different ethnic backgrounds using a seven-dimension learning style scale were tested. Using a comparison of student learning style results against instructor learning style result, and student final grade, the observed learning style score resulted in an identifiable group of first-year students. Further, there is a procedure to enhance success for this group

Question Driven Introductory Programming Instruction: A Pilot Study

For most beginners, learning computer programming is a complex undertaking. Demotivation and learned helplessness have been widely reported. In addition to the subject’s complexity, low in-class involvement has been linked to poor student performance. This work introduces a novel instructional technique called Student-Driven Probe Instruction (SDPI) to address the low levels of in-class involvement in basic programming courses. The concept was straightforward: rather than the teacher lecturing/explaining material to the class and requesting questions, the students were shown a piece of code or other relevant material and given the opportunity to ask questions first. Explanations followed only after the questions had been asked, not before. Participation was tracked through two metrics: the number of questions asked in class and emails/Slack contacts with the instructor. Significant improvements were recorded for in-class participation. Average quiz scores also improved meaningfully. According to a course evaluation survey, students favored SDPI over the conventional lecture format since it piqued their interest in the material and gave them the confidence to ask questions in class

Thinking in imperative or objects? A study on how novice programmer thinks when it comes to designing an application

Novice programming is a challenging subject to teach and learn. However, programming is an essential skill that is required by many majors apart from Computer Science. The challenges in a novice programming subject change according to the programming language used. At the beginning of the 90s, the object-oriented programming was introduced. Detienne claimed that it is easier for programmers to program using the object-first approach as humans think naturally in objects. The IEEE and ACM joint task force on Computing Curriculum proposed two tracks of curriculum, one for imperative-first and the other for objectfirst implementation. However, most of the work conducted on novice programming focused on the issues of syntax errors, reducing the possibilities of syntax error through a new or adapted programming environment. This paper will present the preliminary work to investigate if students will naturally think in objects or a series of steps. Three intervention methods were implemented in three different workshops. The intervention methods are the object-first, the imperative-first and the problem-solving-first. The students are then requested to design an application. Through the design, the research will identify if the students use the object-first or the imperative-first design. Assuming that the object-first intervention group will design primarily in objects, and the imperative-first intervention group in a series of steps, the problem-solving intervention will be the ”neutral” group. The object-first design is reflected through the attributes and methods of a particular object. The imperative-first design is identified if the solution contains a series of steps. The findings show that most of the students designed the application using a series of steps reflecting the imperative-first design. This finding should be included when considering if imperative-first or object-first should be the way forward for a novice programming subject

A Study of Attrition and the Use of Student Learning Communities in the Computer Science Introductory Programming Sequence

Student attrition and low graduation rates are critical problems in computer science education. Disappointing graduation rates and declining student interest have caught the attention of business leaders, researchers and universities. With weak graduation rates and little interest in scientific computing, many are concerned about the nation\u27s ability to meet current demands and to remain competitive, both in product development and technological advances. This dissertation targeted student attrition in the first year of college by studying the impact of learning communities on freshmen computer science students. Several factors including class size, technology in the classroom, and active learning environments were infused into groups in the study to determine the impact on student grades and persistence

Factors Affecting the Student Persistence in Online Education: A Qualitative and Quantitative Investigation

Online education has been gaining popularity thanks to the advent of the Internet. There has been success in providing online education to many students who otherwise would not have had access to higher education. However, many students were dropping out of the online program. In addition, only a few studies have looked at this phenomenon closely and intensively for the purely online students. The current study was therefore initiated to not only find the manifest factors of persistence that apply to online students in degree-granting institutions, but also to discover latent structures and linkages among those factors. The study is unique and vigorous in that it used two methods of data collection and two methods of data analysis. The data collection methods were content analysis and questionnaire, and the two data analysis methods were qualitative and quantitative techniques. A content analysis of over 500 research studies was performed to identify the factors that affect student persistence from the body of literature. The factors were submitted in a survey to faculty members who teach online courses, with a request for comments and/or addition to the list. The resulting list from the two data collection methods was then used in a survey of online students to determine what factors were important to them for persisting in the online program. Qualitative analysis of data was conducted through open coding with the help of a content analysis software. Quantitative analyses were performed which included descriptive statistics as well as three multivariate techniques (i.e., factor analysis, cluster analysis, and multi-dimensional scaling). The latent structure discovered in the study categorized the factors into four groups, namely, personal commitment, social support, institutional commitment and academic confidence. The findings of the study have significant pedagogical, technical, and administrative implications for online education. In pedagogy, the factors found in academic confidence and institutional commitment can be used to enhance persistence-promoting programs, courses, and projects. Implications in technology come from the institutional commitment factors that can be applied to HCI, user experience, and the development of supporting devices and applications. The administration of online education can benefit from factors in personal commitment and social support

Effects of Learning Communities on Community College Students\u27 Success: A Meta-Analysis

Low graduation rates are a significant issue for colleges. The majority of higher education institutions in the United States offer learning communities (LCs), which have been found to be effective for improving course success and persisting to the next semester. However, there is a gap in the literature regarding the effectiveness of LCs with different types of populations and different types of LCs. The purpose of this meta-analysis was to identify the most effective types of LCs. Research questions addressed the effects of different types of LCs on different student success outcomes for community colleges. The study was based on Tinto\u27s interactionist model of student departure and Astin\u27s model of student involvement. Studies examining the relationship between student success and participation in college LCs provided the data for the meta-analysis. A random effects model was used to generate the average effect size for 39 studies and 50 individual effect sizes. The results showed that LCs are most effective with community college students when they include additional support strategies, counseling is available to students, one of the linked courses is an academic skills course, at least one of the linked course is developmental, and the focus is on increasing course success or student engagement. The implications for positive social change suggest that LC programs implement two linked courses, include an academic skills course, focus on developmental courses, and provide access to a counselor and additional student support strategies. In addition, LC programs are most effective when the goals of the program are student engagement and course success