Motivational profiles and their correlates among students in virtual school foreign language courses
Motivation is a key factor in predicting K‐12 students' online learning success. Drawing on self‐determination theory, this study used a person‐centered approach to identify the motivational profiles of students taking online high school language courses, and to examine such profiles' rela...
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| Veröffentlicht in: | British journal of educational technology 2020-03, Vol.51 (2), p.515-530 |
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| container_title | British journal of educational technology |
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| creator | Zhang, Yining Lin, Chin‐Hsi |
| description | Motivation is a key factor in predicting K‐12 students' online learning success. Drawing on self‐determination theory, this study used a person‐centered approach to identify the motivational profiles of students taking online high school language courses, and to examine such profiles' relationships to their learning outcomes, genders and reasons for enrollment. Cluster analysis of 466 students revealed the existence of four profiles: high and low quantity, and good and poor quality. Students in the high‐quantity profile demonstrated comparable learning outcomes to those in the good quality profile; and there was significant gender and enrollment reason differences across the four motivational profiles.
Practitioner Notes
What is already known about this topic
Motivation is of considerable importance to the success of online learning.
Autonomous motivation is more adaptive than controlled motivation.
Most studies have used a variable‐centered approach to investigating the unique and independent roles of motivation types in online learning.
What this paper adds
This study is believed to be the first to use a person‐centered approach to identify motivational profiles (ie, good quality, high quantity, low quantity and poor quality) among virtual‐school students taking foreign‐language courses.
It confirms the positive effect of autonomous motivation on learning, and extends exploration of this effect to online learning.
Students in the high‐quantity profile achieved comparable learning outcomes to those in the good quality profile.
Females were overrepresented in the good quality profile (ie, more females than would be expected by chance).
Motivational profiles differed significantly across enrollment reasons (ie, credit recovery, elective or requirement).
Implications for practice and/or policy
Teachers should not simply place each student in a box as having either autonomous or controlled motivation.
Online learning content and activities should be designed in ways that promote autonomous motivation.
Online educators need to be aware of potential gender and enrollment reason effects on students' motivations. |
| doi_str_mv | 10.1111/bjet.12871 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2355826230</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ericid>EJ1243792</ericid><sourcerecordid>2355826230</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3231-8e3bf5211bd5b2591a62b5fe5fee10ed1ca9885bc320ac8c120e71567b09a5de3</originalsourceid><addsrcrecordid>eNp9kM1LAzEQxYMoWKsX70LAm7A1kzT7cdRSP0rFSz0v2d3Zbcp2U5Nspf-9qSseDYEwmd97zDxCroFNIJz7YoN-AjxN4ISMYBonUSqFPCUjxlgSAQNxTi6c24SSCTkdkerNeL1XXptOtXRnTa1bdFR1FfVr1JaWxlpslT9-bk3XUOf7CjvvqO7oXlvfB50r18a0tDYWddPRVnVNrxoM4t46dJfkrFatw6vfd0w-nuar2Uu0fH9-nT0so1JwAVGKoqglBygqWXCZgYp5IWsMF4FhBaXK0lQWgWaqTEvgDBOQcVKwTMkKxZjcDr5hj88enc83YYCwmMu5kDLlMRcsUHcDVVrjnMU631m9VfaQA8uPKebHFPOfFAN8M8BodfkHzhfApyLJeOjD0P8KuR3-ccofF_PV4PkNkdaAFA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2355826230</pqid></control><display><type>article</type><title>Motivational profiles and their correlates among students in virtual school foreign language courses</title><source>Wiley Online Library Journals Frontfile Complete</source><source>EBSCOhost Education Source</source><creator>Zhang, Yining ; Lin, Chin‐Hsi</creator><creatorcontrib>Zhang, Yining ; Lin, Chin‐Hsi</creatorcontrib><description>Motivation is a key factor in predicting K‐12 students' online learning success. Drawing on self‐determination theory, this study used a person‐centered approach to identify the motivational profiles of students taking online high school language courses, and to examine such profiles' relationships to their learning outcomes, genders and reasons for enrollment. Cluster analysis of 466 students revealed the existence of four profiles: high and low quantity, and good and poor quality. Students in the high‐quantity profile demonstrated comparable learning outcomes to those in the good quality profile; and there was significant gender and enrollment reason differences across the four motivational profiles.
Practitioner Notes
What is already known about this topic
Motivation is of considerable importance to the success of online learning.
Autonomous motivation is more adaptive than controlled motivation.
Most studies have used a variable‐centered approach to investigating the unique and independent roles of motivation types in online learning.
What this paper adds
This study is believed to be the first to use a person‐centered approach to identify motivational profiles (ie, good quality, high quantity, low quantity and poor quality) among virtual‐school students taking foreign‐language courses.
It confirms the positive effect of autonomous motivation on learning, and extends exploration of this effect to online learning.
Students in the high‐quantity profile achieved comparable learning outcomes to those in the good quality profile.
Females were overrepresented in the good quality profile (ie, more females than would be expected by chance).
Motivational profiles differed significantly across enrollment reasons (ie, credit recovery, elective or requirement).
Implications for practice and/or policy
Teachers should not simply place each student in a box as having either autonomous or controlled motivation.
Online learning content and activities should be designed in ways that promote autonomous motivation.
Online educators need to be aware of potential gender and enrollment reason effects on students' motivations.</description><identifier>ISSN: 0007-1013</identifier><identifier>EISSN: 1467-8535</identifier><identifier>DOI: 10.1111/bjet.12871</identifier><language>eng</language><publisher>Coventry: Wiley-Blackwell</publisher><subject>Cluster analysis ; Correlation ; Course Selection (Students) ; Distance learning ; Educational Technology ; Electronic Learning ; Females ; Foreign language instruction ; Foreign language learning ; Foreign languages ; Gender Differences ; High School Students ; Learning outcomes ; Machine learning ; Motivation ; Multivariate Analysis ; Online Courses ; Predictor Variables ; Profiles ; Quality ; Second Language Instruction ; Student Characteristics ; Student Motivation ; Student teacher relationship ; Students ; Success ; Teaching Methods</subject><ispartof>British journal of educational technology, 2020-03, Vol.51 (2), p.515-530</ispartof><rights>2019 British Educational Research Association</rights><rights>2020 British Educational Research Association</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3231-8e3bf5211bd5b2591a62b5fe5fee10ed1ca9885bc320ac8c120e71567b09a5de3</citedby><cites>FETCH-LOGICAL-c3231-8e3bf5211bd5b2591a62b5fe5fee10ed1ca9885bc320ac8c120e71567b09a5de3</cites><orcidid>0000-0001-5468-9702 ; 0000-0002-4730-0671</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fbjet.12871$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fbjet.12871$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttp://eric.ed.gov/ERICWebPortal/detail?accno=EJ1243792$$DView record in ERIC$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhang, Yining</creatorcontrib><creatorcontrib>Lin, Chin‐Hsi</creatorcontrib><title>Motivational profiles and their correlates among students in virtual school foreign language courses</title><title>British journal of educational technology</title><description>Motivation is a key factor in predicting K‐12 students' online learning success. Drawing on self‐determination theory, this study used a person‐centered approach to identify the motivational profiles of students taking online high school language courses, and to examine such profiles' relationships to their learning outcomes, genders and reasons for enrollment. Cluster analysis of 466 students revealed the existence of four profiles: high and low quantity, and good and poor quality. Students in the high‐quantity profile demonstrated comparable learning outcomes to those in the good quality profile; and there was significant gender and enrollment reason differences across the four motivational profiles.
Practitioner Notes
What is already known about this topic
Motivation is of considerable importance to the success of online learning.
Autonomous motivation is more adaptive than controlled motivation.
Most studies have used a variable‐centered approach to investigating the unique and independent roles of motivation types in online learning.
What this paper adds
This study is believed to be the first to use a person‐centered approach to identify motivational profiles (ie, good quality, high quantity, low quantity and poor quality) among virtual‐school students taking foreign‐language courses.
It confirms the positive effect of autonomous motivation on learning, and extends exploration of this effect to online learning.
Students in the high‐quantity profile achieved comparable learning outcomes to those in the good quality profile.
Females were overrepresented in the good quality profile (ie, more females than would be expected by chance).
Motivational profiles differed significantly across enrollment reasons (ie, credit recovery, elective or requirement).
Implications for practice and/or policy
Teachers should not simply place each student in a box as having either autonomous or controlled motivation.
Online learning content and activities should be designed in ways that promote autonomous motivation.
Online educators need to be aware of potential gender and enrollment reason effects on students' motivations.</description><subject>Cluster analysis</subject><subject>Correlation</subject><subject>Course Selection (Students)</subject><subject>Distance learning</subject><subject>Educational Technology</subject><subject>Electronic Learning</subject><subject>Females</subject><subject>Foreign language instruction</subject><subject>Foreign language learning</subject><subject>Foreign languages</subject><subject>Gender Differences</subject><subject>High School Students</subject><subject>Learning outcomes</subject><subject>Machine learning</subject><subject>Motivation</subject><subject>Multivariate Analysis</subject><subject>Online Courses</subject><subject>Predictor Variables</subject><subject>Profiles</subject><subject>Quality</subject><subject>Second Language Instruction</subject><subject>Student Characteristics</subject><subject>Student Motivation</subject><subject>Student teacher relationship</subject><subject>Students</subject><subject>Success</subject><subject>Teaching Methods</subject><issn>0007-1013</issn><issn>1467-8535</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kM1LAzEQxYMoWKsX70LAm7A1kzT7cdRSP0rFSz0v2d3Zbcp2U5Nspf-9qSseDYEwmd97zDxCroFNIJz7YoN-AjxN4ISMYBonUSqFPCUjxlgSAQNxTi6c24SSCTkdkerNeL1XXptOtXRnTa1bdFR1FfVr1JaWxlpslT9-bk3XUOf7CjvvqO7oXlvfB50r18a0tDYWddPRVnVNrxoM4t46dJfkrFatw6vfd0w-nuar2Uu0fH9-nT0so1JwAVGKoqglBygqWXCZgYp5IWsMF4FhBaXK0lQWgWaqTEvgDBOQcVKwTMkKxZjcDr5hj88enc83YYCwmMu5kDLlMRcsUHcDVVrjnMU631m9VfaQA8uPKebHFPOfFAN8M8BodfkHzhfApyLJeOjD0P8KuR3-ccofF_PV4PkNkdaAFA</recordid><startdate>202003</startdate><enddate>202003</enddate><creator>Zhang, Yining</creator><creator>Lin, Chin‐Hsi</creator><general>Wiley-Blackwell</general><general>Blackwell Publishing Ltd</general><scope>7SW</scope><scope>BJH</scope><scope>BNH</scope><scope>BNI</scope><scope>BNJ</scope><scope>BNO</scope><scope>ERI</scope><scope>PET</scope><scope>REK</scope><scope>WWN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7T9</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-5468-9702</orcidid><orcidid>https://orcid.org/0000-0002-4730-0671</orcidid></search><sort><creationdate>202003</creationdate><title>Motivational profiles and their correlates among students in virtual school foreign language courses</title><author>Zhang, Yining ; Lin, Chin‐Hsi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3231-8e3bf5211bd5b2591a62b5fe5fee10ed1ca9885bc320ac8c120e71567b09a5de3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Cluster analysis</topic><topic>Correlation</topic><topic>Course Selection (Students)</topic><topic>Distance learning</topic><topic>Educational Technology</topic><topic>Electronic Learning</topic><topic>Females</topic><topic>Foreign language instruction</topic><topic>Foreign language learning</topic><topic>Foreign languages</topic><topic>Gender Differences</topic><topic>High School Students</topic><topic>Learning outcomes</topic><topic>Machine learning</topic><topic>Motivation</topic><topic>Multivariate Analysis</topic><topic>Online Courses</topic><topic>Predictor Variables</topic><topic>Profiles</topic><topic>Quality</topic><topic>Second Language Instruction</topic><topic>Student Characteristics</topic><topic>Student Motivation</topic><topic>Student teacher relationship</topic><topic>Students</topic><topic>Success</topic><topic>Teaching Methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Yining</creatorcontrib><creatorcontrib>Lin, Chin‐Hsi</creatorcontrib><collection>ERIC</collection><collection>ERIC (Ovid)</collection><collection>ERIC</collection><collection>ERIC</collection><collection>ERIC (Legacy Platform)</collection><collection>ERIC( SilverPlatter )</collection><collection>ERIC</collection><collection>ERIC PlusText (Legacy Platform)</collection><collection>Education Resources Information Center (ERIC)</collection><collection>ERIC</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Linguistics and Language Behavior Abstracts (LLBA)</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>British journal of educational technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Yining</au><au>Lin, Chin‐Hsi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><ericid>EJ1243792</ericid><atitle>Motivational profiles and their correlates among students in virtual school foreign language courses</atitle><jtitle>British journal of educational technology</jtitle><date>2020-03</date><risdate>2020</risdate><volume>51</volume><issue>2</issue><spage>515</spage><epage>530</epage><pages>515-530</pages><issn>0007-1013</issn><eissn>1467-8535</eissn><abstract>Motivation is a key factor in predicting K‐12 students' online learning success. Drawing on self‐determination theory, this study used a person‐centered approach to identify the motivational profiles of students taking online high school language courses, and to examine such profiles' relationships to their learning outcomes, genders and reasons for enrollment. Cluster analysis of 466 students revealed the existence of four profiles: high and low quantity, and good and poor quality. Students in the high‐quantity profile demonstrated comparable learning outcomes to those in the good quality profile; and there was significant gender and enrollment reason differences across the four motivational profiles.
Practitioner Notes
What is already known about this topic
Motivation is of considerable importance to the success of online learning.
Autonomous motivation is more adaptive than controlled motivation.
Most studies have used a variable‐centered approach to investigating the unique and independent roles of motivation types in online learning.
What this paper adds
This study is believed to be the first to use a person‐centered approach to identify motivational profiles (ie, good quality, high quantity, low quantity and poor quality) among virtual‐school students taking foreign‐language courses.
It confirms the positive effect of autonomous motivation on learning, and extends exploration of this effect to online learning.
Students in the high‐quantity profile achieved comparable learning outcomes to those in the good quality profile.
Females were overrepresented in the good quality profile (ie, more females than would be expected by chance).
Motivational profiles differed significantly across enrollment reasons (ie, credit recovery, elective or requirement).
Implications for practice and/or policy
Teachers should not simply place each student in a box as having either autonomous or controlled motivation.
Online learning content and activities should be designed in ways that promote autonomous motivation.
Online educators need to be aware of potential gender and enrollment reason effects on students' motivations.</abstract><cop>Coventry</cop><pub>Wiley-Blackwell</pub><doi>10.1111/bjet.12871</doi><tpages>16</tpages><orcidid>https://orcid.org/0000-0001-5468-9702</orcidid><orcidid>https://orcid.org/0000-0002-4730-0671</orcidid></addata></record> |
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| ispartof | British journal of educational technology, 2020-03, Vol.51 (2), p.515-530 |
| issn | 0007-1013 1467-8535 |
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| source | Wiley Online Library Journals Frontfile Complete; EBSCOhost Education Source |
| subjects | Cluster analysis Correlation Course Selection (Students) Distance learning Educational Technology Electronic Learning Females Foreign language instruction Foreign language learning Foreign languages Gender Differences High School Students Learning outcomes Machine learning Motivation Multivariate Analysis Online Courses Predictor Variables Profiles Quality Second Language Instruction Student Characteristics Student Motivation Student teacher relationship Students Success Teaching Methods |
| title | Motivational profiles and their correlates among students in virtual school foreign language courses |
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