1,721,006 research outputs found
Re-thinking Student Written Comments in Course Evaluations: Text Mining Unstructured Data for Program and Institutional Assessment
Get PDFA nearly ubiquitous instrument of assessment for instructors and courses at the university and community college is the student course evaluation. One common feature of course evaluations is the open-ended questions that are often used to provide feedback to instructors on course and instructional content. Because of the difficulty in large scale assessment of written text, the written comments are often not analyzed with a systematic or consistent methodology. Technological advances, however, have made it possible to quantitatively study the unstructured data from these written responses through the algorithmic use of text and data mining. This study, using 835 surveys from a continuing education program over a five-year period, employed an embedded correlational model using text mining methods such as Principle Component Analysis (PCA) and Singular Value Decomposition (SVD) within a qualitative framework to determine the viability of such an analysis on an institutional level. The study's major findings show that while there is only a weak correlation between the Likert responses and the open-ended written portion, there are significant words and patterns within the unstructured data that provide additional information at the institutional level. The results of this research suggest a need to rethink the design, implementation, and approach to the student course survey that can take advantage of text mining as an analytical tool for the institution
Re-thinking Student Written Comments in Course Evaluations: Text Mining Unstructured Data for Program and Institutional Assessment
Get PDFA nearly ubiquitous instrument of assessment for instructors and courses at the university and community college is the student course evaluation. One common feature of course evaluations is the open-ended questions that are often used to provide feedback to instructors on course and instructional content. Because of the difficulty in large scale assessment of written text, the written comments are often not analyzed with a systematic or consistent methodology. Technological advances, however, have made it possible to quantitatively study the unstructured data from these written responses through the algorithmic use of text and data mining. This study, using 835 surveys from a continuing education program over a five-year period, employed an embedded correlational model using text mining methods such as Principle Component Analysis (PCA) and Singular Value Decomposition (SVD) within a qualitative framework to determine the viability of such an analysis on an institutional level. The study's major findings show that while there is only a weak correlation between the Likert responses and the open-ended written portion, there are significant words and patterns within the unstructured data that provide additional information at the institutional level. The results of this research suggest a need to rethink the design, implementation, and approach to the student course survey that can take advantage of text mining as an analytical tool for the institution
Keeping Faculty [Happy]: The Critical Role of a Faculty Center in Developing and Retaining Quality, Collegial Faculty
Get PDFThis paper describes an innovative approach to retaining happy and healthy faculty members in a collegial, productive teaching and learning environment. A major portion of the paper shares how the Faculty Center for Teaching and Learning plays a significant role in the faculty interview process, new faculty orientation, and subsequent mentoring of new faculty into a collegial environment that supports aligning research with instruction
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
MOOC Observations Using a Modified F2F Quality Teaching Rubric
No full textMassive Open Online Courses (MOOCs) have attracted interest from consumers, academics, and venture capitalists. Attention has been given to infrastructure, marketing, and finance. MOOCs participation has grown to engage over 15 million learners and millions of investment dollars. Although hundreds of thousands have enrolled, completion rate is represented by single digit percentages. Reasons for low completion include lack of time, low self-regulated learning, material is too elevated or foundational, and for some, the quality of instruction is severely lacking. This study explores the concept of quality and how it can be translated from what we know about high quality face-to-face (F2F) teaching into large-scale online teaching. The study uses a modified quality-teaching rubric by Chism (1999) to evaluate 21 MOOCs selected randomly from the Coursera offerings taught in January 2015. The courses included business, technology, education, science, law, music and the liberal arts.
Results indicate that most (81%) of the courses did not attend to quality attributes. The data resulted in a bimodal distribution with only four of the 21 courses observed to offer high quality attributes at least 70% of the time. Recommendations to address current MOOC shortcomings are provided
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