Curricular Analytics in Higher Education

The dissertation addresses different aspects of student success in higher education. Numerous factors may impact a student\u27s ability to succeed and ultimately graduate, including pre-university preparation, as well as the student support services provided by a university. However, even the best efforts to improve in these areas may fail if other institutional factors overwhelm their ability to facilitate student progress. This dissertation addresses this issue from the perspective of curriculum structure. The structural properties of individual curricula are studied, and the extent to which this structure impacts student progress is explored. The structure of curricula are studied using actual university data and analyzed by applying different data mining techniques, machine learning methods and graph theory. These techniques and methods provide a mathematical tool to quantify the complexity of a curriculum structure. The results presented in this work show that there is an inverse correlation between the complexity of a curriculum and the graduation rate of students attempting that curriculum. To make it more practical, this study was extended further to implement a number of predictive models that give colleges and universities the ability to track the progress of their students in order to improve retention and graduation rates. These models accurately predict the performance of students in subsequent terms and accordingly could be used to provide early intervention alerts. The dissertation addresses another important aspect related to curricula. Specifically, how course enrollment sequences in a curriculum impact student progress. Thus, graduation rates could be improved by directing students to follow better course sequences. The novelty of the models presented in this dissertation is characterized in introducing graduation rate, for the first time in literature, from the perspective of curricular complexity. This provides the faculty and staff the ability to better advise students earlier in their academic careers

Curriculum Complexity and Graduation Rates at Utah State University

This study utilizes a curricular analytics framework developed by Heileman et al. (2018) to examine the relationship between curriculum complexity and graduation rates in academic programs at Utah State University. The goal in quantifying the complexity of curricula is to determine whether or not prerequisite courses and other factors of curricula structure impacts graduation from the university. To accomplish this goal, curriculum complexity spreadsheets were developed for 96 degree programs at the university, which facilitated the assignment of curriculum complexity scores to the 6,337 students who qualified for the quasi-experimental study. Logistic regression was then applied to the resulting data to plot graduation trends for students who graduated within four, five, and six years across the spectrum of curriculum complexity scores. The resulting trendlines indicate that increased curriculum complexity at Utah State University is significantly associated with lower graduation rates and calls for program administrators to restructure prerequisite structures to enable increased degree completion

Development of a Curriculum Analysis and Simulation Library with Applications in Curricular Analytics

Higher education institutions are currently investing significant resources in attempts to improve student success by improving instruction quality, implementing tutoring programs, and providing other services to help students. While these are all worth- while, one area that tends to be overlooked is the structure of the curricula that are offered. When viewing curricula as data, or more specifically, a graph, it is intuitive to see how its structure can influence a student’s ability to move through it. How- ever, there are currently no tools to analyze a curriculum’s structural properties and how they might affect student success. This thesis describes a software library that was developed to address this issue by providing the ability to represent curricula in a programming environment as well as a set of tools to evaluate the complexity of curricula and simulate students moving through them. Furthermore, the application of these tools are shown through several experiments that demonstrate a negative correlation between a curriculum’s complexity and student success

A Quantitative Assessment and Comparison of the Undergraduate Curriculum Prerequisite Structures for the Universities in the Minnesota State System with Particular Emphasis on Mathematics Courses

The purpose of this dissertation is to study the consistency of the structures and the centrality of mathematics courses in the curricula of the universities in the Minnesota State University system. This research will be based on the curriculum prerequisite networks for the seven universities in the Minnesota State System. These networks will be constructed from the information in the course catalogs available on each university’s public website. The networks will be constructed with courses represented by nodes and weighted edges representing prerequisite relationships. The analysis will use curriculum network analytics to evaluate and compare the connectedness of the networks, the centrality of mathematics courses, and the importance of mathematics departments in the structure of each university’s curriculum

Curricular Optimization: Solving for the Optimal Student Success Pathway

Considering the significant investment of higher education made by students and their families, graduating in a timely manner is of the utmost importance. Delay attributed to drop out or the retaking of a course adds cost and negatively affects a student’s academic progression. Considering this, it becomes paramount for institutions to focus on student success in relation to term scheduling. Often overlooked, complexity of a course schedule may be one of the most important factors in whether or not a student successfully completes his or her degree. More often than not students entering an institution as a first time full time (FSFT) freshman follow the advised and published schedule given by administrators. Providing the optimal schedule that gives the student the highest probability of success is critical. In efforts to create this optimal schedule, this thesis introduces a novel optimization algorithm with the objective to separate courses which when taken together hurt students’ pass rates. Inversely, we combine synergistic relationships that improve a students probability for success when the courses are taken in the same semester. Using actual student data at the University of Kentucky, we categorically find these positive and negative combinations by analyzing recorded pass rates. Using Julia language on top of the Gurobi solver, we solve for the optimal degree plan of a student in the electrical engineering program using a linear and non-linear multi-objective optimization. A user interface is created for administrators to optimize their curricula at main.optimizeplans.com

Exploring the Strategies of Raising Motivation among ESL students in a non-English speaking context

Motivation, undoubtedly, plays a very crucial role in any learning process including second and foreign language learning. Such cruciality positions the maintaining and motivation raising in the integral part of learning and more so in the currently growing and more technologically advanced learning environments. This paper conceptually discussed the motivation raising strategies which have been employed toward English as second language (ESL) learners in two different dimensions, which are those strategies which depend on the role of an ESL teacher (i.e. pedagogical and material selection) and those which do not (i.e. parents, school institutions, media, and gender difference). Despite the existence of other external factors, we argue that teacher plays the decisive role on ESL learners’ motivation. From the critical review and more extended discussion, it is found that teacher’s awareness toward the cruciality of students’ motivation influences the strategies used by the teachers in order to raise motivation. The paper also re-emphasises the urgent needs for a more learner-centred learning as it is believed to have positive impact for learners’ motivation. This paper concludes by highlighting the significant contributions of the insights discussed within this study, especially for ESL teaching practitioners

Utilizing Institutional Data for Curriculum Enhancement to Improve Student Success in Undergraduate Computing Programs

Student success is one of the widely discussed topics in post-secondary institutions and is measured in terms of the graduation and retention rates of programs. The goal of an educational institution is to achieve maximum student success and, hence, high graduation and retention rates. There are multiple studies on factors affecting student success. One of the factors that contributes to student success is the program curriculum. Unfortunately, the traditional program curricula at many higher education institutions were developed with a belief or assumption that all students possess equal expertise, skills, and follow a similar learning path. The traditional curricular development process neglects some specifics related to the characteristics of transfer and the First Time In College (FTIC) students and their time to graduation. The purpose of this research was to explore the relationship between the traditional program curricula and student degree mobility patterns to measure student success of transfer and FTIC students enrolled in Computer Science, Information Technology, and Computer Engineering undergraduate academic programs as well as how those relationships assist in the development and reform processes of curricula. This study was designed to understand the various aspects of program curricula, such as impacts of a program-specific factor, prerequisite, and post-requisite course requirements on time to graduation. This study leads to the development of Adaptive Curriculum Refinement, a novel approach based on institutional data analytics to assist higher education curriculum designers in the data-driven development of new curricula and data-driven revision of existing ones. The results of this study suggest a direct relationship between the curricular stringency and student time to graduation, whereas stringency was inversely related to the credit accumulation. The program-specific factor in the curriculum directly affects students\u27 time to graduation. This study is significant because the results and the development of Adaptive Curriculum Refinement could inform higher education policymakers and assist curriculum designers about the need to reform program curricula based on a data-driven and evidence-based approach to improve student success

Improving graduate attributes within the Egyptian university sector.

Throughout the years universities have attempted to foster graduate attributes in undergraduate degree courses. Despite the initiatives and funds put in place, attempts have been met with limited success causing what is known as the skills gap. This study sets out to understand the causes underpinning the skills gap by examining the specific nature of graduate attributes through using complexity theory. It builds on earlier work into graduate attributes by investigating the reasons influencing the variation in their interpretation thus providing an analysis of their contextual nature. Rather than determining key factors, this paper examines the multi factor causalities that affect the teaching and learning of graduate attributes in their educational context which requires to be acknowledged in higher education policies and practices. The study was explored in the Egyptian computer engineering undergraduate context. Using semi-structured interviews, a number of questions were posed to a purposive sample of academics and graduates belonging to two different computer engineering undergraduate programmes; one that is private and another that is public. To ensure the validity of data, more data were collected from Egyptian employers as well as the documents that represent the different educational policies and practices implemented in both private and public programmes of study. This research could be of interest to higher education authorities including: universities, deans of faculties, and heads of academic programmes, academics teaching undergraduate bachelor degrees, and course designers and reviewers for undergraduate bachelor degrees

A comparative analysis of British and Saudi approaches to counter radicalisation: Engaging the Muslim community as a model

This study compares the capacity of Saudi Arabia and Britain to engage their communities in counter-extremism, through the introduction of an original theoretical model of analysis. The thesis argues that active community engagement may serve as a critical indicator of counter-extremist efficiency. The theoretical framework is applied to the radicalisation of Muslim communities in both countries, with specific focuses on the roles of four critical elements in counter-radicalisation: religious figures, women, young individuals, and educational institutions. Drawing on a wide range of interviews, government documents, and other primary and secondary sources, the thesis presents several key insights, which are divided into three interlinked categories. First, the significance of engaging the four main societal components. Second, how community engagement can be enhanced by means of three linear concepts: trust-building, warning people and encouraging them to participate in counter-extremism, and training participants. Third, how this participation can be influenced by three factors: local cultures, external effects, and political systems and their foreign policies. This study demonstrates both British and Saudi weaknesses in reaching individuals and convincing them to participate in counter-extremist efforts