Sequence Of Courses Research Articles

Extending curricular analytics to analyze undergraduate physics programs

Curricular analytics (CA) is a quantitative method that analyzes the sequence of courses (curriculum) that students in an undergraduate academic program must complete to fulfill the requirements of the program. The main hypothesis of CA is that the less complex a curriculum is, the more likely it is that students complete the program. This study compares the curricular complexity of undergraduate physics programs at 60 institutions in the United States. The institutions were divided into three tiers based on national rankings of the physics graduate program, and the means of each tier were compared. No significant difference between the means of each tier was found, indicating that there is not a relationship between program curricular complexity and program ranking. Further analysis focused on the physics, chemistry, and mathematics courses, defined as the core courses of the curriculum. Significant differences in the number of required core courses and the complexity per core course were measured between the tiers; both were measured as large effects. Programs with the highest rankings required fewer core courses while having a higher complexity per core course. These institutions have more strict prerequisite requirements than lower ranking programs. This study also showed complexity was quantitatively related to curricular flexibility operationalized as the number of available eight-semester degree plans. The number of available degree plans exponentially decreased with increasing core complexity per course. Modifications to a curriculum at one institution were analyzed; a similar relationship between the number of available degree plans and increasing complexity per core course was found. Published by the American Physical Society 2024

Major curricula as structures for disciplinary acculturation that contribute to student minoritization

Institutions of higher learning are characterized by multiple, often intersecting, social-educational structures aimed at regulating the conditions by which a degree is ultimately granted. The sequence of courses that students must take for a degree is one such structure. Building on the Sloan Equity and Inclusion in STEM Introductory Courses (SEISMIC) Collaboration’s prior work, we provide a comparative view of students’ pathways through selected curricula at two participating institutions. We apply process analytics to students’ course enrollments as a tool to reveal features of the curricula and the associated impacts on students’ progressions to degree. Given the high enrollment in biology-related degree programs at these institutions, we focus on those and ask two questions: (1) Is the intended progression through the curriculum the one most commonly experienced by the students? and (2) does the maintenance of coherence and socialization into the discipline act in a similar way on individuals of different socio, economic and demographic backgrounds? Curriculum analytics tends to be driven by a reductionist view of its structure. Instead, we view the curriculum as a tool for disciplinary acculturation, revealing aspects of students’ transitions through educational systems not captured by commonly applied course or retention analyses. Curricular structures and the constraints they impose impact the way individual students become members of a scholarly community by acting as a cultural and social homogenizing agent. Across the curricula and institutions in this study, we find that this process results in minoritization, hampering student progression through the curriculum and contributing to disciplinary exclusion in favor of traditionally advantaged socio-demographic groups. We call for curricular restructuring that (1) reduces or alters the depth of the hierarchical course sequences, changing the way progression is established; and (2) encourages adoption of pedagogical approaches in the courses that adapt to the learning community to which they cater; ultimately incorporating an asset-based approach to the acquisition of knowledge inclusive of students’ diversity of backgrounds, experiences, and ways of being.

What Is the Impact of Major Diversion Attitude on Undergraduates' Learning Gains？ ——The Mediating Role of Course Perception

Major diversion is an important part of the large-category student enrollment and training model. The extent to which undergraduates recognize the rationality of the major diversion system, their satisfaction with the diverted major, and their major identity after diversion affect their subsequent learning process and results. The questionnaire survey of undergraduates in this study found that major diversion attitude has a significant positive effect on undergraduates' learning gains; the mediating effect test found that course perception plays a partially mediating role between major diversion attitude and learning gains. Therefore, under the large-category student enrollment and training model, it is necessary to improve the major diversion system in terms of the formulation of diversion system, the guidance of major selection and the promotion of major identity. Furthermore, strengthening the logical connection and content coupling of different types of courses, dealing with the proportion, priority and sequence of courses, optimizing the allocation of course resources, reasonable planning and setting courses also play an important role in improving learning gains of undergraduates.

On that most over Skinned of Improper Integrals

Summary Continuing a much discussed topic of the various ways a particular improper integral can be evaluated, we give three further ways its generalization can be evaluated. Using techniques typically encountered immediately after the calculus sequence of courses we show how the improper integral can be evaluated using the beta and gamma functions, by first converting it to a double integral, and using a property of the Laplace transform.

Redesign of a First-Year Theory Course Sequence in Biostatistics

This communication describes the process and results of a curriculum review of a first-year sequence of courses in statistical inference within a Master of Biostatistics program. Our primary aim was to develop an innovative course in statistical theory that meets the needs of a diverse student audience, the majority of whom are seeking a terminal master’s degree while a minority will pursue PhD training in biostatistics. The main results were (1) different course paths for job-bound and PhD-bound students; and (2) the development of an innovative first course in statistical inference, which is a computationally-aided self-discovery of a salient (albeit not comprehensive) set of key concepts and techniques pertaining to statistical inference. The redesign process addressed a key conceptual barrier: namely, the unexamined assumption that deductive proofs are a necessary condition for rigorous presentation. Consistent with the principles of constructivism, we navigated this barrier by redefining the task to which pedagogic rigor should be applied: namely, to help students to develop a sound mental map of statistical inference. We believe that the approach we used to accomplish this redefined task could be generalized to additional aspects of statistical education, among others.

Towards AI-powered data-driven education

Educational platforms are increasingly becoming AI-driven. Besides providing a wide range of course filtering options, personalized recommendations of learning material and teachers are driving today's research. While accuracy plays a major role in evaluating those recommendations, many factors must be considered including learner retention, throughput, upskilling ability, equity of learning opportunities, and satisfaction. This creates a tension between learner-centered and platform-centered approaches. I will describe research at the intersection of data-driven recommendations and education theory. This includes multi-objective algorithms that leverage collaboration and affinity in peer learning, studying the impact of learning strategies on platforms and people, and automating the generation of sequences of courses. The paper ends with a discussion of the central role data management systems could play in enabling modern online education.

Path Analysis to Determine the Effect of Learning Outcomes of Prerequisite Mathematics on Expert Systems Courses

The study background is the need to evaluate learning and the placement of the sequence of courses. The learning objectives are achieved optimally. This study conducts a path analysis to determine the direct or indirect effect of learning outcomes for mathematics prerequisite courses, Discrete Mathematics and Linear Algebra and Matrix, on learning outcomes of Expert Systems with Artificial Intelligence as an intervening variable. This study is explanatory research conducted at the Study Program of Informatics Engineering, STMIK Palangkaraya. The sample used is the 2017 and 2018 batch of students who have taken and passed the MD, AL, KB, and SP courses, as many as 94 people. The data were analyzed using student learning outcomes in the four courses. The data were then selected and analyzed descriptively, the assumption of path analysis (normality, multicollinearity, and heteroscedasticity) was tested, and finally, path analysis was performed. Hypothesis testing was carried out with the help of the R program. The results showed (1) the learning outcomes of the MD and AL courses directly significantly affected the learning outcomes of the KB courses by 23% and 23.7%, respectively, and (2) the learning outcomes of the AL courses directly affected the learning outcomes of the SP courses by 34.9%, (3) the learning outcomes for MD and KB courses do not directly affect learning outcomes for SP courses, (4) learning outcomes for MD and AL courses do not indirectly affect learning outcomes for SP courses.

Course Recommendation based on Sequences: An Evolutionary Search of Emerging Sequential Patterns

To provide a good study plan is key to avoid students’ failure. Academic advising based on student’s preferences, complexity of the semester, or even background knowledge is usually considered to reduce the dropout rate. This article aims to provide a good course index to recommend courses to students based on the sequence of courses already taken by each student. Hence, unlike existing long-term course planning methods, it is based on graduate students to model the course and not on external factors that might introduce some bias in the process. The proposal includes a novel sequential pattern mining algorithm, called (ES)^2P (Evolutionary Search of Emerging Sequential Patterns), that properly identifies paths followed by good students and not followed by not so good students, as a long-term course planning approach. A major feature of the proposed (ES)^2P algorithm is its ability to extract the best k solutions, that is, those with a best recommendation index score instead of returning the whole set of solutions above a predefined threshold. A real study case is performed including more than 13,000 students belonging to 13 faculties to demonstrate the usefulness of the proposal not only to recommend study plans but also to give advices at different stages of the students’ learning process.

Recovering the Story of Pragmatism in India: Bhimrao Ambedkar, John Dewey, and the Origins of Navayana Pragmatism

Recovering the Story of Pragmatism in India: Bhimrao Ambedkar, John Dewey, and the Origins of Navayana Pragmatism

A Mixture Hidden Markov Model to Mine Students’ University Curricula

In the context of higher education, the wide availability of data gathered by universities for administrative purposes or for recording the evolution of students’ learning processes makes novel data mining techniques particularly useful to tackle critical issues. In Italy, current academic regulations allow students to customize the chronological sequence of courses they have to attend to obtain the final degree. This leads to a variety of sequences of exams, with an average time taken to obtain the degree that may significantly differ from the time established by law. In this contribution, we propose a mixture hidden Markov model to classify students into groups that are homogenous in terms of university paths, with the aim of detecting bottlenecks in the academic career and improving students’ performance.

Second chance schools: background, training and current instructional practices of teachers

PurposeThe objective of the present study was to assess which teachers hired to teach secondary school dropouts are most likely to adapt their practices to match their students' characteristics. Chile recently initiated a system “second chance” schools for dropouts. Most of the teaching staff were recruited from the secondary schools from which the students had withdrawn. There was little variation in instructional practices or schedules. The second chance schools provide intensive instruction, small classes and flexibility in schedules and sequence of courses. The study sought to identify the teachers most likely to adapt old practices or learn new ones in order to provide students a different educational experience than that offered in conventional secondary schools.Design/methodology/approachThe sampling design for this study was developed by the Statistics Department of the Ministry of Education. Taking enrollment into account, they randomly selected second chance schools from 13 of Chile's 16 regions. Then, they randomly selected 617 teachers from 38 of the selected schools. The teachers were invited to respond to a self-administered survey questionnaire that covered beliefs about and attitudes toward dropouts, and frequency of use of different teaching methods. The analytical procedures used include nonparametric correlations and logit regression.FindingsTeaching methods in the second chance schools are influenced mostly by type of in-service training and not by student characteristics. Most teachers expect most students to graduate; teachers with more years of teaching are the least optimistic.Originality/valueRelatively little research on second chance schools has been published in Latin America. The Second Opportunity Schools are the first effort in Chile to provide public secondary school to dropouts. The study provides detailed information about background and training linked to current teachers' instructional practices. The findings suggest actions that can be taken to improve the new schools.

Contrasting undergraduate mathematics students’ approaches to learning and their interactions within two student-centred learning environments

The Students’ Approaches to Learning (SAL) tradition comprehends an approach to learning as a combination of students’ aims for learning and the processes used to achieve them. The tradition values a deep approach to learning; this is the case also in the context of university mathematics, where a deep approach is seen as a requirement for learning proof-based mathematics. However, supporting a deep approach through learning environments has turned out to be a complex endeavour. The present study addresses this complexity by qualitatively contrasting the same students’ approaches learning in two pedagogically different undergraduate mathematics learning environments. The study is a follow-up on a quantitative study and reports on 16 student interviews aiming to connect the students’ quantitatively determined approaches to learning with their aims for learning and the actualized learning processes within the learning environments. The results suggest that student subgroups with different approaches to learning are distinguished by their aims for learning, and based on the students’ own reporting, by the ability to reflect on learning and utilize student collaboration. We discuss the results and conclude that a sequence of courses with well-aligned instructional practices is needed to support the development of a deep approach to learning.

Supporting Student Success and Persistence in STEM With Active Learning Approaches in Emerging Scholars Classrooms

Over the last several decades, Emerging Scholars Programs (ESPs) have incorporated active learning strategies and challenging problems into collegiate mathematics, resulting in students, underrepresented minority (URM) students in particular, earning at least half of a letter grade higher than other students in Calculus. In 2009, West Virginia University (WVU) adapted ESP models for use in Calculus I in an effort to support the success and retention of URM STEM students by embedding group and inquiry-based learning into a designated section of Calculus I. Seats in the class were reserved for URM and first-generation students. We anticipated that supporting students in courses in the calculus sequence, including Calculus I, would support URM Calculus I students in building learning communities and serve as a mechanism to provide a strong foundation for long-term retention. In this study we analyze the success of students that have progressed through our ESP Calculus courses and compare them to their non-ESP counterparts. Results show that ESP URM students succeed in the Calculus sequence at substantially higher rates than URM students in non-ESP sections of Calculus courses in the sequence (81% of URM students pass ESP Calculus I while only 50% of URM students pass non-ESP Calculus I). In addition, ESP URM and ESP non-URM (first-generation but not URM) students succeed at similar levels in the ESP Calculus sequence of courses (81% of URM students and 82% of non-URM students pass ESP Calculus I). Finally, ESP URM students’ one-year retention rates are similar to those of ESP non-URM students and significantly higher than those of URM students in non-ESP sections of Calculus (92% of ESP URM Calculus I students were retained after one year, while only 83% of URM non-ESP Calculus I students were retained). These results suggest that ESP is ideally suited for retaining and graduating URM STEM majors, helping them overcome obstacles and barriers in STEM, and increasing diversity, equity, and inclusion in Calculus.

A simultaneous sequencing and allocation problem for military pilot training: Integer programming approaches

In this paper, we study a unique, rich combinatorial optimization problem that arose from helicopter aircrew training for the Royal Australian Navy. Each pilot trainee (student) has to complete a syllabus. A syllabus is a sequence of courses (commonly known as subjects), and each course is associated with a pass rate. A pre-requisite structure exists amongst some courses. Each course has a number of repeated sessions, each spanning the same amount of time, but occupying a different set of (possibly overlapping) time slots. A feasible schedule is a sequence of course sessions such that each course in the syllabus is covered by exactly one session, and that all pre-requisite requirements are observed. The optimization problem is to simultaneously assemble course sessions to form feasible schedules, allocate students to these schedules with an objective to minimize the total time-span in completing the syllabus, while ensuring that the class size limits for each course session is not exceeded. The problem is different from the school or university time tabling family of problems due to the assembly component required. This paper is to serve as a pilot study: we derive a number of mixed-integer linear programming models and investigate their performance using test instances provided for us by our industry partner. For each of these models, we propose a number of solution strategies as topics for future research papers. From our numerical testing, it appears that the Column Generation-based approach is computationally the most promising method.

Intelligent Support System for Personalized Online Learning

The current conditions of the COVID-19 pandemic have required universities to transfer educational processes in the online environment. eLearning systems provide educational institutions and students with the opportunity to effectively organize the educational process and share knowledge. They provide each student with freedom of access to information and flexibility of the learning process. The student can individually determine the duration and sequence of courses by changing the trajectory of the educational process following their needs. In the context of the pandemic, students and teachers have to optimize their work over the Internet. This requires more extended personalization of the learning process. Intelligent technologies allow you to construct personalized learning paths for each student, varying methods, forms, and speed of learning. This study presents the architecture of the e-learning support system for the selection of online resources and for including them in the student's learning path. The system developed as a set of personal agents and services that interact based on a set of interconnected ontological models. Ontologies provide a more adequate representation of online resources and compatibility of the user request format with descriptions of training resources from different developers. The system recommends training modules based on current requests and user characteristics that match their profile. The system dynamically updates the knowledge base user characteristics, thereby increasing the effectiveness of recommendations.

Formation of Professional Competence of Future Officers of the Logistics Troops (Forces) Supply of the Armed Forces of Ukraine

The purpose of the article is to identify the essence and basic principles of formation of professional competence of future logistics officers of the Armed Forces of Ukraine, to determine the algorithm of formation of professional competence by stages of professional training in the higher military educational institution, to identify methods and techniques corresponding to logistics. Research methods: theoretical analysis of primary sources, normative documents, conceptual principles of logistics; systematization, modeling, observation and testing. The results of the analysis revealed that the professional competence of future logistics officers is a personal education and an integral characteristic, which includes key and general competencies that are the result of training in higher military educational institution, covering the dynamic set of knowledge, skills and experience in this specialty, personal and socially significant qualities (ways of thinking, ability to self-study, learning styles, views, values, nature of behavior in unpredictable conditions, etc.) arising on the basis of the formed subject competences and provide an opportunity to perform the military logistics officer’s duties and professional tasks effectively. The principles of forming the professional competence of future logistics officers corresponding to their specialty as they are basic both in military-economic, and in pedagogical logistics are defined. These are: principle of systematization, principle of functionality, principle of integration and integrated goal setting, principle of «just in time», principle of «jit-reliability», principle of solving information problems by standardizing data, principle of prioritizing the needs of learners, principle of variability of strategies, methods and techniques, principle of focusing on the end result, principle of interaction of all components of the professional competence formation system, principle of coordination of actions of different divisions specialists. The influence of these principles on the formation of the future logistics officers’ professional competence is analyzed. An algorithm for the formation of professional competence was developed, which was modeled according to two opposite approaches – directions (direct and reverse): «bottom up», it means by stages of professional training in higher military educational institution – a sequence of courses, semesters and levels of training (bachelor, master) of future officers; and «top-down», it means from the principles of professional competence formation through the construction of a «goal tree» and the definition of its components (key competencies) and their manifestations in the material of subjects that form general subject competencies, to building a «competence tree» and designing them for each discipline and definition of subject competencies. There are a number of teaching methods and techniques that take into account the specifics of logistics, such as: methods of empirical adult learning, problem-based learning, the method of planned mistakes, visualization methods, methods of press conferences, dialogue, discussions, brainstorming techniques, case studies, which should be used in the educational process to form the professional competence of future logistics officers. Conclusions: the purpose of the study is achieved.

Curriculum mapping in academic libraries revisited: Taking an evidence-based approach

Curriculum mapping for the purposes of an academic library is the process of reviewing a degree-granting department’s curriculum side-by-side with library learning objectives to situate information literacy instruction within the sequence of courses that a student will take.In 2014, I undertook a curriculum mapping pilot for our library using a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis methodology as part of a leadership institute. My project looked at three degree programs at our university and suggested changes for further engagement with the departments. At the same time, three other librarians that I met at the leadership institute took part in curriculum mapping projects at their institutions using different methodologies. Together, we published our results in the New Review of Academic Librarianship.

Teaching Introductory Statistics with DataCamp

We designed a sequence of courses for the DataCamp online learning platform that approximates the content of a typical introductory statistics course. We discuss the design and implementation of these courses and illustrate how they can be successfully integrated into a brick-and-mortar class. We reflect on the process of creating content for online consumers, ruminate on the pedagogical considerations we faced, and describe an R package for statistical inference that became a by-product of this development process. We discuss the pros and cons of creating the course sequence and express our view that some aspects were particularly problematic. The issues raised should be relevant to nearly all statistics instructors. Supplementary materials for this article are available online.

Introduction

Introduction Andrew Gibb (bio) In the places where the craft of theatre is taught as part of a college or university curriculum, requirements often include some exposure to the history of the field, whether offered through a designated course or sequence of courses, or in a more integrated fashion within classes intended to teach acting, design, directing, or any number of production-related skills. The intentions behind this requirement are frequently multiple, dependent on the unique mission of the institution and the population(s) it serves. One frequently expressed goal of history coursework is the fostering of a sense of artistic and professional community through the inculcation of what is conceived as a common genealogical narrative. Such an argument may be borrowed, consciously or not, from the rhetoric advanced to support the teaching of national history as a key component of primary and secondary education. In the case of theatre history instruction, a traditional practice (though by no means a universal one, and a habit that has been increasingly challenged in the last few decades) is to begin the assumed common narrative with the study of the drama and theatrical practice of fifth-century bce Athens. A statement frequently made by textbooks and instructors alike regarding performance in that place and time is that the ancient Athenians considered attendance at, or sponsorship of, theatrical festivals to be something akin to a civic duty—an activity that declared one’s citizenship.1 Perhaps this embrace of an origin story that places theatre at the center of civic discourse is the result of a sense of injustice, as theatre makers often believe that they are being treated as second-class citizens within the halls of academia. What better claim of relevance could be made than to [End Page 5] point out (however accurately or Eurocentrically) that theatre began in the cradle of democracy and philosophy? Despite the strategic usefulness of this particular historical claim, however, when the long arc of history is considered, are theatre folk truly justified in claiming a fundamental connection between theatre and citizenship? No doubt the editors of and contributors to this volume would answer that question affirmatively, though it is worth noting that our stance is likely dependent upon a broader definition of “citizenship” than might be endorsed by other academic or legal traditions. The call for the scholarly conference from which this publication emerged was circulated in the waning months of 2018, following a summer of urgent and emotional debate surrounding new US immigration policies regarding immigrant family separations, arguments fueled on one side by fears about the loss of social cohesion, and on the other by photographs of incarcerated children.2 Given the then-prevailing political atmosphere, the present editor anticipated that a good number of submissions might draw connections between the patterns, policies, and histories of immigration on the one hand, and theatrical or otherwise performance-centered expressions of citizenship, whether inclusive or exclusionary, on the other. In retrospect, what could have been foreseen is that theatre scholars, educators, and professionals would interpret recent events against a wider and more complex backdrop. The ultimate result of that initial call is the work you now hold in your hand, a collection of essays whose authors reach beyond simple definitions of citizenship as determined by documents and legal rights, and who engage in larger conversations about what citizenship can mean, and how such meanings are expressed through theatre and performance. Interestingly, while none of the authors published herein take up immigration as a central issue, they all make use of some combination of three particular analytical frameworks, all of which happen to be pertinent to the current immigrant experience and attempts to regulate it: bodies, institutions, and technologies. A focus on bodies in performance (whether the physical bodies of humans, animatronic figures, or puppets, or the less tangible examples of bodies of literary work or digitally embodied presences) represents in part a continuation of the rich conversation surrounding “Theatre and Embodiment” distilled by editor Sarah McCarroll into the publication of last year’s volume of Theatre Symposium. Institutions (here taking the form of theatres, schools, prize boards, and theme parks) have always been of interest...

Theoretical basis of integrative approaches studying of STEM-education programs implementation in secondary educational institutions of Ukraine

The article examines integrative approaches of educational STEM programs implementation in secondary educational institutions. The concept of “STEM education” is not stable. The views of experts on its content are revealed through such generalized components as pedagogical technology (pedagogical process), focus on practical tasks and problem-based learning. At the same time, integrative approaches find application in the disciplines, the sequence of courses, and in a separate course. Generalization of the definitions of the concept “STEM education”, proposed by various experts, made it possible to understand it as a joint activity, interaction and cooperation of teachers, students and stakeholders, aimed at overcoming the fragmentation of knowledge by eliminating boundaries between them, integrating content components. It provides the formation of key competencies necessary for further employment and life activity in the conditions of the formation and development of new branches of knowledge. The article describes the general features of the learning organization in accordance with disciplinary, multidisciplinary, interdisciplinary and transdisciplinary approaches. In the context of transdisciplinarity, the prospects for the development of educational programs in secondary educational institutions of Ukraine is considered. It is possible to single out a number of problems accompanying the process of STEM courses developing and implementing. There are the problem of systematizing the structural and logical links between disciplines to be merged, the problem of professional readiness of teachers specializing in teaching one or two disciplines to take responsibility for mentoring and supporting student’s transdisciplinary projects and modernization of educational laboratories and making of modern STEM centres at secondary educational institution.