Predicting statistics performance beyond statistics anxiety

Statistics anxiety has been the focus of past researchers seeking to improve students’ statistics performance. Recent research has challenged the widely-held assumption that statistics anxiety would negatively predict statistics performance. This study investigated the predictive value of goal orien...

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Main Author: Kwek, Kenneth Shuan Gui
Other Authors: Ho Moon-Ho Ringo
Format: Final Year Project
Language:English
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/10356/70539
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-705392019-12-10T12:17:13Z Predicting statistics performance beyond statistics anxiety Kwek, Kenneth Shuan Gui Ho Moon-Ho Ringo School of Humanities and Social Sciences DRNTU::Social sciences::Statistics Statistics anxiety has been the focus of past researchers seeking to improve students’ statistics performance. Recent research has challenged the widely-held assumption that statistics anxiety would negatively predict statistics performance. This study investigated the predictive value of goal orientation, statistics self-efficacy, learning strategies, and learning emotions relative to the influence of statistics anxiety on statistics performance. A total of 115 participants completed a questionnaire which included five measures adapted from PALS, MSLQ, CSSE, LRE and STARS. Hierarchical regression analyses revealed that mastery goal orientation and learning hopelessness were the strongest predictors of statistics performance after controlling for “worth of statistics”, self-regulation and pride. Specifically, mastery goal orientation positively predicted statistics performance whereas learning hopelessness negatively predicts statistics performance. Implications for the research of statistics anxiety are discussed and recommendations for interventions by statistics instructors are presented. Bachelor of Arts 2017-04-27T04:55:22Z 2017-04-27T04:55:22Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/70539 en Nanyang Technological University 52 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Social sciences::Statistics
spellingShingle DRNTU::Social sciences::Statistics
Kwek, Kenneth Shuan Gui
Predicting statistics performance beyond statistics anxiety
description Statistics anxiety has been the focus of past researchers seeking to improve students’ statistics performance. Recent research has challenged the widely-held assumption that statistics anxiety would negatively predict statistics performance. This study investigated the predictive value of goal orientation, statistics self-efficacy, learning strategies, and learning emotions relative to the influence of statistics anxiety on statistics performance. A total of 115 participants completed a questionnaire which included five measures adapted from PALS, MSLQ, CSSE, LRE and STARS. Hierarchical regression analyses revealed that mastery goal orientation and learning hopelessness were the strongest predictors of statistics performance after controlling for “worth of statistics”, self-regulation and pride. Specifically, mastery goal orientation positively predicted statistics performance whereas learning hopelessness negatively predicts statistics performance. Implications for the research of statistics anxiety are discussed and recommendations for interventions by statistics instructors are presented.
author2 Ho Moon-Ho Ringo
author_facet Ho Moon-Ho Ringo
Kwek, Kenneth Shuan Gui
format Final Year Project
author Kwek, Kenneth Shuan Gui
author_sort Kwek, Kenneth Shuan Gui
title Predicting statistics performance beyond statistics anxiety
title_short Predicting statistics performance beyond statistics anxiety
title_full Predicting statistics performance beyond statistics anxiety
title_fullStr Predicting statistics performance beyond statistics anxiety
title_full_unstemmed Predicting statistics performance beyond statistics anxiety
title_sort predicting statistics performance beyond statistics anxiety
publishDate 2017
url http://hdl.handle.net/10356/70539
_version_ 1681048560902078464