{"title":"AN OUTCOME-BASED STATISTICAL CAPACITY DEVELOPMENT PROGRAMME TO SUPPORT RESEARCH AT A UNIVERSITY","authors":"Enriqueta D. Reston, E. S. Poliquit","doi":"10.52041/SERJ.V19I1.129","DOIUrl":null,"url":null,"abstract":"This paper addresses a critical component of the infrastructure necessary for professional development toward more effective teaching and learning of research and statistical methods. In particular, an interdisciplinary in-service model is proposed, which has the potential to better prepare educators to address institution-specific needs amidst dwindling resources. In particular, we present an outcome-based model for developing statistical capacity in research in response to the need for training statisticians in the academia. The aim of the programme was to equip selected faculty with the competencies needed to provide various forms of statistical support services in line with the research, extension, and publication mandate of a large private university in the Philippines. The programme was administered in three phases: (1) training phase, (2) statistical consulting and mentoring phase, and (3) “cascading or extension” phase. Evaluation of the outcome involves participants’ demonstration of learning in various statistical methods through serving as resource persons during the cascading activity and the documentation of the statistical consulting experiences made during the programme. \nFirst published February 2020 at Statistics Education Research Journal Archives","PeriodicalId":38581,"journal":{"name":"Statistics Education Research Journal","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics Education Research Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52041/SERJ.V19I1.129","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 1
Abstract
This paper addresses a critical component of the infrastructure necessary for professional development toward more effective teaching and learning of research and statistical methods. In particular, an interdisciplinary in-service model is proposed, which has the potential to better prepare educators to address institution-specific needs amidst dwindling resources. In particular, we present an outcome-based model for developing statistical capacity in research in response to the need for training statisticians in the academia. The aim of the programme was to equip selected faculty with the competencies needed to provide various forms of statistical support services in line with the research, extension, and publication mandate of a large private university in the Philippines. The programme was administered in three phases: (1) training phase, (2) statistical consulting and mentoring phase, and (3) “cascading or extension” phase. Evaluation of the outcome involves participants’ demonstration of learning in various statistical methods through serving as resource persons during the cascading activity and the documentation of the statistical consulting experiences made during the programme.
First published February 2020 at Statistics Education Research Journal Archives
期刊介绍:
SERJ is a peer-reviewed electronic journal of the International Association for Statistical Education (IASE) and the International Statistical Institute (ISI). SERJ is published twice a year and is free. SERJ aims to advance research-based knowledge that can help to improve the teaching, learning, and understanding of statistics or probability at all educational levels and in both formal (classroom-based) and informal (out-of-classroom) contexts. Such research may examine, for example, cognitive, motivational, attitudinal, curricular, teaching-related, technology-related, organizational, or societal factors and processes that are related to the development and understanding of stochastic knowledge. In addition, research may focus on how people use or apply statistical and probabilistic information and ideas, broadly viewed. The Journal encourages the submission of quality papers related to the above goals, such as reports of original research (both quantitative and qualitative), integrative and critical reviews of research literature, analyses of research-based theoretical and methodological models, and other types of papers described in full in the Guidelines for Authors. All papers are reviewed internally by an Associate Editor or Editor, and are blind-reviewed by at least two external referees. Contributions in English are recommended. Contributions in French and Spanish will also be considered. A submitted paper must not have been published before or be under consideration for publication elsewhere.