Validating curriculum development using text mining

Interdisciplinarity requires the collaboration of two or more disciplines to combine their expertise to jointly develop and deliver learning and teaching outcomes appropriate for a subject area. Curricula and assessment mapping are critical components to foster and enhance interdisciplinary learning environments. Emerging careers in data science and machine learning coupled with the necessary graduate outcomes mandate the need for a truly interdisciplinary pedagogical approach. The challenges for emerging academic disciplines such as data science and machine learning center on the need for multiple fields to coherently develop university-level curricula. Using text mining, we empirically analyze the breadth and depth of existing tertiary-level curricula to quantify patterns in curricula through the use of surface and deep cluster analysis. This approach helps educators validate the breadth and depth of a proposed curriculum relative to the broad evolution of data science as a discipline.     

Description and evaluation of methods for the learning of interpersonal,transferable and management skills by students of animal science

Abstract

An Interpersonal, Transferable and Management Skills course, scheduled for one morning per week over a period of 9 weeks, and offered to final year students of animal science, is described. Nine team exercises with the objective of allowing skills development are detailed. A further eight sessions were devoted to meetings between students and visitors of substance and importance with distant but tendentious links to the students. Learning outcomes were examined by questionnaires addressing twenty-three IT skills. The course appeared to have been successful in achieving substantial positive change in the skills of reviewing and measuring one's own performance, problem-solving, decision-making, team work, sensitivity to others, assertiveness, presenting spoken information, understanding and reviewing the work of others, self-confidence, and initiative. Positive change was also identified for the skills of target setting, prioritisation, negotiation, and self-knowledge. But the course achieved little or no effective change in the skills of working to schedule, listening, or absorbing spoken information. These latter elements are presently receiving attention, as are gender issues and the needs of postgraduate research students.     

Teaching data science: an objective approach to curriculum validation

Emerging careers in technology-focused fields such as data science coupled with necessary graduate outcomes mandate the need for a truly interdisciplinary pedagogical approach. However, the rapid pace of curriculum development in this field of inquiry has meant that curricula across universities has largely evolved in line with the internal disciplinary strengths of each institution rather than in response to the needs of graduates. To assist with the development of data science subjects the themes and content that contribute to each subject should be objectively validated. We propose the use of an objective test for data science curricula to quantify whether a particular degree programme maintains an interdisciplinary perspective unconstrained by single discipline bias. The test analyses a given curriculum and quantifies the subject components by category using natural language processing (NLP) techniques.     

Motivation for Educational Attainment in Grade 9 Predicts High School Completion

The Motivation for Educational Attainment (MEA) questionnaire, developed to assess facets related to early adolescents’ motivation to complete high school, has a bifactor structure with a large general factor and three smaller orthogonal specific factors (teacher expectations, peer aspirations, value of education). This prospective validity study investigated the utility of each factor in predicting high school dropout or completion of a general education development (GED) certificate versus completion of a high school degree. Participants were 474 (55.1% male) ethnically diverse students who were originally recruited into a larger longitudinal study in Grade 1 on the basis of academic risk. Fourteen years later, 373 had obtained a high school diploma, 15 had obtained a GED, and 86 had dropped out of high school. During their first year of Grade 9, participants were administered the MEA. Using multinomial logistic regression with high school graduation as the reference outcome and controlling for Grade 9 letter grades, reading and math test scores, gender, and ethnic/racial group status, scores on the latent general factor and the latent peer aspirations factor predicted high school dropout versus high school graduation status. Neither the general factor nor any of the three specific factors predicted GED completion versus high school graduation. Ethnicity, but not gender, moderated the associations between scores on the general factor and high school graduation versus dropout.     

THE KNOWLEDGE OF MEMORY AGING QUESTIONNAIRE

A new questionnaire, the Knowledge of Memory Aging Questionnaire, assesses general knowledge of normal and pathological memory aging for use with students, older adults, and service providers who work with the elderly. The questionnaire consists of 28 true/false items covering a broad range of memory behaviors     

School Governors—an effective management force or another bureaucratic layer of school management?

This paper reviews the pattern and organisation of governors' meetings and their effectiveness for managing the new environment established by the 1988 Education Reform Act. It suggests that the move towards a sub‐committee structure may be counter‐productive in educational terms. A different approach is put forward which may be more appropriate for primary and most secondary governing bodies. The paper goes on to suggest a training strategy which facilitates the team approach that it is necessary for the partners in the process, i.e. governors, head and officers/advisers, to adopt. This draws heavily on the training approach adopted in Leicestershire.     

Mendeley: Creating Communities of Scholarly Inquiry Through Research Collaboration

Mendeley is a free, web-based tool for organizing research citations and annotating their accompanying PDF articles. Adapting Web 2.0 principles for academic scholarship, Mendeley integrates the management of the research articles with features for collaborating with researchers locally and worldwide. In this article the features of Mendeley are discussed and critiqued in comparison to other, similar tools. These features include citation management, online synchronization and collaboration, PDF management and annotation, and integration with word processing software. The article concludes with a discussion of how a social networking tool such as Mendeley might impact the academic scholarship process.