Making a #Stepchange? Investigating the Alignment of Learning Analytics and Student Wellbeing in United Kingdom Higher Education Institutions
In recent years there has been growing concern around student wellbeing and in particular student mental-health. Numerous newspaper articles (Ferguson, 2017; Shackle, 2019) have been published on the topic and a BBC 3 documentary (Byrne, 2017) was produced on the topic of student suicide. These have...
Ausführliche Beschreibung
Autor*in: |
Samantha J. Ahern [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
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2020 |
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Übergeordnetes Werk: |
In: Frontiers in Education - Frontiers Media S.A., 2017, 5(2020) |
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Übergeordnetes Werk: |
volume:5 ; year:2020 |
Links: |
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DOI / URN: |
10.3389/feduc.2020.531424 |
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Katalog-ID: |
DOAJ006612547 |
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520 | |a In recent years there has been growing concern around student wellbeing and in particular student mental-health. Numerous newspaper articles (Ferguson, 2017; Shackle, 2019) have been published on the topic and a BBC 3 documentary (Byrne, 2017) was produced on the topic of student suicide. These have coincided with a number of United Kingdom Higher Education sector initiatives and reports, the highest profile of these being the Universities United Kingdom “#StepChange” report (Universities UK, 2017) and the Institute for Public Policy Research “Not By Degrees” report (“Not by Degrees: Improving Student Mental Health in the UK’s Universities” 2017). Simultaneously, learning analytics has been growing as a field in the United Kingdom, with a number of institutions running services predominantly based on student retention and progression, the majority of which make use of the Jisc Learning Analytics service. Much of the data used in these services is behavioral data: interactions with various IT systems, attendance at events and/or engagement with library services. Wellbeing research indicates that since changes in wellbeing, are indicated by changes in behavior, these changes could be identified via learning analytics. Research has also shown that students react very emotively to learning analytics data and that this may impact on their wellbeing. The 2017 Universities United Kingdom (UUK) #StepChange report states: “Institutions are encouraged to align learning analytics to the mental health agenda to identify change in students’ behaviors and to address risks and target support.” (Universities UK, 2017). This study was undertaken in the 2018/19 academic year, a year after the launch of the #StepChange framework and after the formal transition of Jisc’s learning analytics work with partner HEIs to a national learning analytics service. With further calls for whole institutional responses to address student wellbeing and mental health concerns, including the recently published University Mental Health Charter this study aims to answer two questions. Firstly, is there evidence of the #StepChange recommendation being adopted in current learning analytics implementations? Secondly, has there been any consideration of the impact on staff and student wellbeing and mental health resulting from the introduction of learning analytics? Analysis of existing learning analytics applications have found that there is insufficient granularity in the data used to be able to identify changes in an individual’s behavior at a required level, in addition this data is collected with insufficient context to be able to truly understand what the data represents. Where there are connections between learning analytics and student support these are related to student retention and academic performance. Although it has been identified that learning analytics can impact on student and staff behaviors, there is no evidence of staff and student wellbeing being considered in current policies or in the existing policy frameworks. The recommendation from the 2017 Stepchange framework has not been met and reviews of current practices need to be undertaken if learning analytics is to be part of Mentally Healthy Universities moving forward. In conclusion, although learning analytics is a growing field and becoming operationalized within United Kingdom Higher Education it is still in its reactive infancy. Current data models rely on proxies for student engagement and may not truly represent student behaviors. At this time there is inadequate sophistication for the use of learning analytics to identify student wellbeing concerns. However, as with all technologies, learning analytics is not benign, and changes to ways of working impact on both staff and students, wellbeing professionals should be included as key stakeholders in the development of learning analytics and student support policies and wellbeing considerations explicitly mentioned and taken into account. | ||
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10.3389/feduc.2020.531424 doi (DE-627)DOAJ006612547 (DE-599)DOAJ3001bd307fc24fbfa7eb5e96e1f426fd DE-627 ger DE-627 rakwb eng L7-991 Samantha J. Ahern verfasserin aut Making a #Stepchange? Investigating the Alignment of Learning Analytics and Student Wellbeing in United Kingdom Higher Education Institutions 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In recent years there has been growing concern around student wellbeing and in particular student mental-health. Numerous newspaper articles (Ferguson, 2017; Shackle, 2019) have been published on the topic and a BBC 3 documentary (Byrne, 2017) was produced on the topic of student suicide. These have coincided with a number of United Kingdom Higher Education sector initiatives and reports, the highest profile of these being the Universities United Kingdom “#StepChange” report (Universities UK, 2017) and the Institute for Public Policy Research “Not By Degrees” report (“Not by Degrees: Improving Student Mental Health in the UK’s Universities” 2017). Simultaneously, learning analytics has been growing as a field in the United Kingdom, with a number of institutions running services predominantly based on student retention and progression, the majority of which make use of the Jisc Learning Analytics service. Much of the data used in these services is behavioral data: interactions with various IT systems, attendance at events and/or engagement with library services. Wellbeing research indicates that since changes in wellbeing, are indicated by changes in behavior, these changes could be identified via learning analytics. Research has also shown that students react very emotively to learning analytics data and that this may impact on their wellbeing. The 2017 Universities United Kingdom (UUK) #StepChange report states: “Institutions are encouraged to align learning analytics to the mental health agenda to identify change in students’ behaviors and to address risks and target support.” (Universities UK, 2017). This study was undertaken in the 2018/19 academic year, a year after the launch of the #StepChange framework and after the formal transition of Jisc’s learning analytics work with partner HEIs to a national learning analytics service. With further calls for whole institutional responses to address student wellbeing and mental health concerns, including the recently published University Mental Health Charter this study aims to answer two questions. Firstly, is there evidence of the #StepChange recommendation being adopted in current learning analytics implementations? Secondly, has there been any consideration of the impact on staff and student wellbeing and mental health resulting from the introduction of learning analytics? Analysis of existing learning analytics applications have found that there is insufficient granularity in the data used to be able to identify changes in an individual’s behavior at a required level, in addition this data is collected with insufficient context to be able to truly understand what the data represents. Where there are connections between learning analytics and student support these are related to student retention and academic performance. Although it has been identified that learning analytics can impact on student and staff behaviors, there is no evidence of staff and student wellbeing being considered in current policies or in the existing policy frameworks. The recommendation from the 2017 Stepchange framework has not been met and reviews of current practices need to be undertaken if learning analytics is to be part of Mentally Healthy Universities moving forward. In conclusion, although learning analytics is a growing field and becoming operationalized within United Kingdom Higher Education it is still in its reactive infancy. Current data models rely on proxies for student engagement and may not truly represent student behaviors. At this time there is inadequate sophistication for the use of learning analytics to identify student wellbeing concerns. However, as with all technologies, learning analytics is not benign, and changes to ways of working impact on both staff and students, wellbeing professionals should be included as key stakeholders in the development of learning analytics and student support policies and wellbeing considerations explicitly mentioned and taken into account. learning analytics policy wellbeing personal tutoring frameworks Education (General) In Frontiers in Education Frontiers Media S.A., 2017 5(2020) (DE-627)878204881 (DE-600)2882397-7 2504284X nnns volume:5 year:2020 https://doi.org/10.3389/feduc.2020.531424 kostenfrei https://doaj.org/article/3001bd307fc24fbfa7eb5e96e1f426fd kostenfrei https://www.frontiersin.org/articles/10.3389/feduc.2020.531424/full kostenfrei https://doaj.org/toc/2504-284X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2044 GBV_ILN_2086 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 5 2020 |
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10.3389/feduc.2020.531424 doi (DE-627)DOAJ006612547 (DE-599)DOAJ3001bd307fc24fbfa7eb5e96e1f426fd DE-627 ger DE-627 rakwb eng L7-991 Samantha J. Ahern verfasserin aut Making a #Stepchange? Investigating the Alignment of Learning Analytics and Student Wellbeing in United Kingdom Higher Education Institutions 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In recent years there has been growing concern around student wellbeing and in particular student mental-health. Numerous newspaper articles (Ferguson, 2017; Shackle, 2019) have been published on the topic and a BBC 3 documentary (Byrne, 2017) was produced on the topic of student suicide. These have coincided with a number of United Kingdom Higher Education sector initiatives and reports, the highest profile of these being the Universities United Kingdom “#StepChange” report (Universities UK, 2017) and the Institute for Public Policy Research “Not By Degrees” report (“Not by Degrees: Improving Student Mental Health in the UK’s Universities” 2017). Simultaneously, learning analytics has been growing as a field in the United Kingdom, with a number of institutions running services predominantly based on student retention and progression, the majority of which make use of the Jisc Learning Analytics service. Much of the data used in these services is behavioral data: interactions with various IT systems, attendance at events and/or engagement with library services. Wellbeing research indicates that since changes in wellbeing, are indicated by changes in behavior, these changes could be identified via learning analytics. Research has also shown that students react very emotively to learning analytics data and that this may impact on their wellbeing. The 2017 Universities United Kingdom (UUK) #StepChange report states: “Institutions are encouraged to align learning analytics to the mental health agenda to identify change in students’ behaviors and to address risks and target support.” (Universities UK, 2017). This study was undertaken in the 2018/19 academic year, a year after the launch of the #StepChange framework and after the formal transition of Jisc’s learning analytics work with partner HEIs to a national learning analytics service. With further calls for whole institutional responses to address student wellbeing and mental health concerns, including the recently published University Mental Health Charter this study aims to answer two questions. Firstly, is there evidence of the #StepChange recommendation being adopted in current learning analytics implementations? Secondly, has there been any consideration of the impact on staff and student wellbeing and mental health resulting from the introduction of learning analytics? Analysis of existing learning analytics applications have found that there is insufficient granularity in the data used to be able to identify changes in an individual’s behavior at a required level, in addition this data is collected with insufficient context to be able to truly understand what the data represents. Where there are connections between learning analytics and student support these are related to student retention and academic performance. Although it has been identified that learning analytics can impact on student and staff behaviors, there is no evidence of staff and student wellbeing being considered in current policies or in the existing policy frameworks. The recommendation from the 2017 Stepchange framework has not been met and reviews of current practices need to be undertaken if learning analytics is to be part of Mentally Healthy Universities moving forward. In conclusion, although learning analytics is a growing field and becoming operationalized within United Kingdom Higher Education it is still in its reactive infancy. Current data models rely on proxies for student engagement and may not truly represent student behaviors. At this time there is inadequate sophistication for the use of learning analytics to identify student wellbeing concerns. However, as with all technologies, learning analytics is not benign, and changes to ways of working impact on both staff and students, wellbeing professionals should be included as key stakeholders in the development of learning analytics and student support policies and wellbeing considerations explicitly mentioned and taken into account. learning analytics policy wellbeing personal tutoring frameworks Education (General) In Frontiers in Education Frontiers Media S.A., 2017 5(2020) (DE-627)878204881 (DE-600)2882397-7 2504284X nnns volume:5 year:2020 https://doi.org/10.3389/feduc.2020.531424 kostenfrei https://doaj.org/article/3001bd307fc24fbfa7eb5e96e1f426fd kostenfrei https://www.frontiersin.org/articles/10.3389/feduc.2020.531424/full kostenfrei https://doaj.org/toc/2504-284X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2044 GBV_ILN_2086 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 5 2020 |
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10.3389/feduc.2020.531424 doi (DE-627)DOAJ006612547 (DE-599)DOAJ3001bd307fc24fbfa7eb5e96e1f426fd DE-627 ger DE-627 rakwb eng L7-991 Samantha J. Ahern verfasserin aut Making a #Stepchange? Investigating the Alignment of Learning Analytics and Student Wellbeing in United Kingdom Higher Education Institutions 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In recent years there has been growing concern around student wellbeing and in particular student mental-health. Numerous newspaper articles (Ferguson, 2017; Shackle, 2019) have been published on the topic and a BBC 3 documentary (Byrne, 2017) was produced on the topic of student suicide. These have coincided with a number of United Kingdom Higher Education sector initiatives and reports, the highest profile of these being the Universities United Kingdom “#StepChange” report (Universities UK, 2017) and the Institute for Public Policy Research “Not By Degrees” report (“Not by Degrees: Improving Student Mental Health in the UK’s Universities” 2017). Simultaneously, learning analytics has been growing as a field in the United Kingdom, with a number of institutions running services predominantly based on student retention and progression, the majority of which make use of the Jisc Learning Analytics service. Much of the data used in these services is behavioral data: interactions with various IT systems, attendance at events and/or engagement with library services. Wellbeing research indicates that since changes in wellbeing, are indicated by changes in behavior, these changes could be identified via learning analytics. Research has also shown that students react very emotively to learning analytics data and that this may impact on their wellbeing. The 2017 Universities United Kingdom (UUK) #StepChange report states: “Institutions are encouraged to align learning analytics to the mental health agenda to identify change in students’ behaviors and to address risks and target support.” (Universities UK, 2017). This study was undertaken in the 2018/19 academic year, a year after the launch of the #StepChange framework and after the formal transition of Jisc’s learning analytics work with partner HEIs to a national learning analytics service. With further calls for whole institutional responses to address student wellbeing and mental health concerns, including the recently published University Mental Health Charter this study aims to answer two questions. Firstly, is there evidence of the #StepChange recommendation being adopted in current learning analytics implementations? Secondly, has there been any consideration of the impact on staff and student wellbeing and mental health resulting from the introduction of learning analytics? Analysis of existing learning analytics applications have found that there is insufficient granularity in the data used to be able to identify changes in an individual’s behavior at a required level, in addition this data is collected with insufficient context to be able to truly understand what the data represents. Where there are connections between learning analytics and student support these are related to student retention and academic performance. Although it has been identified that learning analytics can impact on student and staff behaviors, there is no evidence of staff and student wellbeing being considered in current policies or in the existing policy frameworks. The recommendation from the 2017 Stepchange framework has not been met and reviews of current practices need to be undertaken if learning analytics is to be part of Mentally Healthy Universities moving forward. In conclusion, although learning analytics is a growing field and becoming operationalized within United Kingdom Higher Education it is still in its reactive infancy. Current data models rely on proxies for student engagement and may not truly represent student behaviors. At this time there is inadequate sophistication for the use of learning analytics to identify student wellbeing concerns. However, as with all technologies, learning analytics is not benign, and changes to ways of working impact on both staff and students, wellbeing professionals should be included as key stakeholders in the development of learning analytics and student support policies and wellbeing considerations explicitly mentioned and taken into account. learning analytics policy wellbeing personal tutoring frameworks Education (General) In Frontiers in Education Frontiers Media S.A., 2017 5(2020) (DE-627)878204881 (DE-600)2882397-7 2504284X nnns volume:5 year:2020 https://doi.org/10.3389/feduc.2020.531424 kostenfrei https://doaj.org/article/3001bd307fc24fbfa7eb5e96e1f426fd kostenfrei https://www.frontiersin.org/articles/10.3389/feduc.2020.531424/full kostenfrei https://doaj.org/toc/2504-284X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2044 GBV_ILN_2086 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 5 2020 |
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10.3389/feduc.2020.531424 doi (DE-627)DOAJ006612547 (DE-599)DOAJ3001bd307fc24fbfa7eb5e96e1f426fd DE-627 ger DE-627 rakwb eng L7-991 Samantha J. Ahern verfasserin aut Making a #Stepchange? Investigating the Alignment of Learning Analytics and Student Wellbeing in United Kingdom Higher Education Institutions 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In recent years there has been growing concern around student wellbeing and in particular student mental-health. Numerous newspaper articles (Ferguson, 2017; Shackle, 2019) have been published on the topic and a BBC 3 documentary (Byrne, 2017) was produced on the topic of student suicide. These have coincided with a number of United Kingdom Higher Education sector initiatives and reports, the highest profile of these being the Universities United Kingdom “#StepChange” report (Universities UK, 2017) and the Institute for Public Policy Research “Not By Degrees” report (“Not by Degrees: Improving Student Mental Health in the UK’s Universities” 2017). Simultaneously, learning analytics has been growing as a field in the United Kingdom, with a number of institutions running services predominantly based on student retention and progression, the majority of which make use of the Jisc Learning Analytics service. Much of the data used in these services is behavioral data: interactions with various IT systems, attendance at events and/or engagement with library services. Wellbeing research indicates that since changes in wellbeing, are indicated by changes in behavior, these changes could be identified via learning analytics. Research has also shown that students react very emotively to learning analytics data and that this may impact on their wellbeing. The 2017 Universities United Kingdom (UUK) #StepChange report states: “Institutions are encouraged to align learning analytics to the mental health agenda to identify change in students’ behaviors and to address risks and target support.” (Universities UK, 2017). This study was undertaken in the 2018/19 academic year, a year after the launch of the #StepChange framework and after the formal transition of Jisc’s learning analytics work with partner HEIs to a national learning analytics service. With further calls for whole institutional responses to address student wellbeing and mental health concerns, including the recently published University Mental Health Charter this study aims to answer two questions. Firstly, is there evidence of the #StepChange recommendation being adopted in current learning analytics implementations? Secondly, has there been any consideration of the impact on staff and student wellbeing and mental health resulting from the introduction of learning analytics? Analysis of existing learning analytics applications have found that there is insufficient granularity in the data used to be able to identify changes in an individual’s behavior at a required level, in addition this data is collected with insufficient context to be able to truly understand what the data represents. Where there are connections between learning analytics and student support these are related to student retention and academic performance. Although it has been identified that learning analytics can impact on student and staff behaviors, there is no evidence of staff and student wellbeing being considered in current policies or in the existing policy frameworks. The recommendation from the 2017 Stepchange framework has not been met and reviews of current practices need to be undertaken if learning analytics is to be part of Mentally Healthy Universities moving forward. In conclusion, although learning analytics is a growing field and becoming operationalized within United Kingdom Higher Education it is still in its reactive infancy. Current data models rely on proxies for student engagement and may not truly represent student behaviors. At this time there is inadequate sophistication for the use of learning analytics to identify student wellbeing concerns. 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These have coincided with a number of United Kingdom Higher Education sector initiatives and reports, the highest profile of these being the Universities United Kingdom “#StepChange” report (Universities UK, 2017) and the Institute for Public Policy Research “Not By Degrees” report (“Not by Degrees: Improving Student Mental Health in the UK’s Universities” 2017). Simultaneously, learning analytics has been growing as a field in the United Kingdom, with a number of institutions running services predominantly based on student retention and progression, the majority of which make use of the Jisc Learning Analytics service. Much of the data used in these services is behavioral data: interactions with various IT systems, attendance at events and/or engagement with library services. Wellbeing research indicates that since changes in wellbeing, are indicated by changes in behavior, these changes could be identified via learning analytics. Research has also shown that students react very emotively to learning analytics data and that this may impact on their wellbeing. The 2017 Universities United Kingdom (UUK) #StepChange report states: “Institutions are encouraged to align learning analytics to the mental health agenda to identify change in students’ behaviors and to address risks and target support.” (Universities UK, 2017). This study was undertaken in the 2018/19 academic year, a year after the launch of the #StepChange framework and after the formal transition of Jisc’s learning analytics work with partner HEIs to a national learning analytics service. With further calls for whole institutional responses to address student wellbeing and mental health concerns, including the recently published University Mental Health Charter this study aims to answer two questions. Firstly, is there evidence of the #StepChange recommendation being adopted in current learning analytics implementations? Secondly, has there been any consideration of the impact on staff and student wellbeing and mental health resulting from the introduction of learning analytics? Analysis of existing learning analytics applications have found that there is insufficient granularity in the data used to be able to identify changes in an individual’s behavior at a required level, in addition this data is collected with insufficient context to be able to truly understand what the data represents. Where there are connections between learning analytics and student support these are related to student retention and academic performance. Although it has been identified that learning analytics can impact on student and staff behaviors, there is no evidence of staff and student wellbeing being considered in current policies or in the existing policy frameworks. The recommendation from the 2017 Stepchange framework has not been met and reviews of current practices need to be undertaken if learning analytics is to be part of Mentally Healthy Universities moving forward. In conclusion, although learning analytics is a growing field and becoming operationalized within United Kingdom Higher Education it is still in its reactive infancy. Current data models rely on proxies for student engagement and may not truly represent student behaviors. At this time there is inadequate sophistication for the use of learning analytics to identify student wellbeing concerns. 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Making a #Stepchange? Investigating the Alignment of Learning Analytics and Student Wellbeing in United Kingdom Higher Education Institutions |
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In recent years there has been growing concern around student wellbeing and in particular student mental-health. Numerous newspaper articles (Ferguson, 2017; Shackle, 2019) have been published on the topic and a BBC 3 documentary (Byrne, 2017) was produced on the topic of student suicide. These have coincided with a number of United Kingdom Higher Education sector initiatives and reports, the highest profile of these being the Universities United Kingdom “#StepChange” report (Universities UK, 2017) and the Institute for Public Policy Research “Not By Degrees” report (“Not by Degrees: Improving Student Mental Health in the UK’s Universities” 2017). Simultaneously, learning analytics has been growing as a field in the United Kingdom, with a number of institutions running services predominantly based on student retention and progression, the majority of which make use of the Jisc Learning Analytics service. Much of the data used in these services is behavioral data: interactions with various IT systems, attendance at events and/or engagement with library services. Wellbeing research indicates that since changes in wellbeing, are indicated by changes in behavior, these changes could be identified via learning analytics. Research has also shown that students react very emotively to learning analytics data and that this may impact on their wellbeing. The 2017 Universities United Kingdom (UUK) #StepChange report states: “Institutions are encouraged to align learning analytics to the mental health agenda to identify change in students’ behaviors and to address risks and target support.” (Universities UK, 2017). This study was undertaken in the 2018/19 academic year, a year after the launch of the #StepChange framework and after the formal transition of Jisc’s learning analytics work with partner HEIs to a national learning analytics service. With further calls for whole institutional responses to address student wellbeing and mental health concerns, including the recently published University Mental Health Charter this study aims to answer two questions. Firstly, is there evidence of the #StepChange recommendation being adopted in current learning analytics implementations? Secondly, has there been any consideration of the impact on staff and student wellbeing and mental health resulting from the introduction of learning analytics? Analysis of existing learning analytics applications have found that there is insufficient granularity in the data used to be able to identify changes in an individual’s behavior at a required level, in addition this data is collected with insufficient context to be able to truly understand what the data represents. Where there are connections between learning analytics and student support these are related to student retention and academic performance. Although it has been identified that learning analytics can impact on student and staff behaviors, there is no evidence of staff and student wellbeing being considered in current policies or in the existing policy frameworks. The recommendation from the 2017 Stepchange framework has not been met and reviews of current practices need to be undertaken if learning analytics is to be part of Mentally Healthy Universities moving forward. In conclusion, although learning analytics is a growing field and becoming operationalized within United Kingdom Higher Education it is still in its reactive infancy. Current data models rely on proxies for student engagement and may not truly represent student behaviors. At this time there is inadequate sophistication for the use of learning analytics to identify student wellbeing concerns. However, as with all technologies, learning analytics is not benign, and changes to ways of working impact on both staff and students, wellbeing professionals should be included as key stakeholders in the development of learning analytics and student support policies and wellbeing considerations explicitly mentioned and taken into account. |
abstractGer |
In recent years there has been growing concern around student wellbeing and in particular student mental-health. Numerous newspaper articles (Ferguson, 2017; Shackle, 2019) have been published on the topic and a BBC 3 documentary (Byrne, 2017) was produced on the topic of student suicide. These have coincided with a number of United Kingdom Higher Education sector initiatives and reports, the highest profile of these being the Universities United Kingdom “#StepChange” report (Universities UK, 2017) and the Institute for Public Policy Research “Not By Degrees” report (“Not by Degrees: Improving Student Mental Health in the UK’s Universities” 2017). Simultaneously, learning analytics has been growing as a field in the United Kingdom, with a number of institutions running services predominantly based on student retention and progression, the majority of which make use of the Jisc Learning Analytics service. Much of the data used in these services is behavioral data: interactions with various IT systems, attendance at events and/or engagement with library services. Wellbeing research indicates that since changes in wellbeing, are indicated by changes in behavior, these changes could be identified via learning analytics. Research has also shown that students react very emotively to learning analytics data and that this may impact on their wellbeing. The 2017 Universities United Kingdom (UUK) #StepChange report states: “Institutions are encouraged to align learning analytics to the mental health agenda to identify change in students’ behaviors and to address risks and target support.” (Universities UK, 2017). This study was undertaken in the 2018/19 academic year, a year after the launch of the #StepChange framework and after the formal transition of Jisc’s learning analytics work with partner HEIs to a national learning analytics service. With further calls for whole institutional responses to address student wellbeing and mental health concerns, including the recently published University Mental Health Charter this study aims to answer two questions. Firstly, is there evidence of the #StepChange recommendation being adopted in current learning analytics implementations? Secondly, has there been any consideration of the impact on staff and student wellbeing and mental health resulting from the introduction of learning analytics? Analysis of existing learning analytics applications have found that there is insufficient granularity in the data used to be able to identify changes in an individual’s behavior at a required level, in addition this data is collected with insufficient context to be able to truly understand what the data represents. Where there are connections between learning analytics and student support these are related to student retention and academic performance. Although it has been identified that learning analytics can impact on student and staff behaviors, there is no evidence of staff and student wellbeing being considered in current policies or in the existing policy frameworks. The recommendation from the 2017 Stepchange framework has not been met and reviews of current practices need to be undertaken if learning analytics is to be part of Mentally Healthy Universities moving forward. In conclusion, although learning analytics is a growing field and becoming operationalized within United Kingdom Higher Education it is still in its reactive infancy. Current data models rely on proxies for student engagement and may not truly represent student behaviors. At this time there is inadequate sophistication for the use of learning analytics to identify student wellbeing concerns. However, as with all technologies, learning analytics is not benign, and changes to ways of working impact on both staff and students, wellbeing professionals should be included as key stakeholders in the development of learning analytics and student support policies and wellbeing considerations explicitly mentioned and taken into account. |
abstract_unstemmed |
In recent years there has been growing concern around student wellbeing and in particular student mental-health. Numerous newspaper articles (Ferguson, 2017; Shackle, 2019) have been published on the topic and a BBC 3 documentary (Byrne, 2017) was produced on the topic of student suicide. These have coincided with a number of United Kingdom Higher Education sector initiatives and reports, the highest profile of these being the Universities United Kingdom “#StepChange” report (Universities UK, 2017) and the Institute for Public Policy Research “Not By Degrees” report (“Not by Degrees: Improving Student Mental Health in the UK’s Universities” 2017). Simultaneously, learning analytics has been growing as a field in the United Kingdom, with a number of institutions running services predominantly based on student retention and progression, the majority of which make use of the Jisc Learning Analytics service. Much of the data used in these services is behavioral data: interactions with various IT systems, attendance at events and/or engagement with library services. Wellbeing research indicates that since changes in wellbeing, are indicated by changes in behavior, these changes could be identified via learning analytics. Research has also shown that students react very emotively to learning analytics data and that this may impact on their wellbeing. The 2017 Universities United Kingdom (UUK) #StepChange report states: “Institutions are encouraged to align learning analytics to the mental health agenda to identify change in students’ behaviors and to address risks and target support.” (Universities UK, 2017). This study was undertaken in the 2018/19 academic year, a year after the launch of the #StepChange framework and after the formal transition of Jisc’s learning analytics work with partner HEIs to a national learning analytics service. With further calls for whole institutional responses to address student wellbeing and mental health concerns, including the recently published University Mental Health Charter this study aims to answer two questions. Firstly, is there evidence of the #StepChange recommendation being adopted in current learning analytics implementations? Secondly, has there been any consideration of the impact on staff and student wellbeing and mental health resulting from the introduction of learning analytics? Analysis of existing learning analytics applications have found that there is insufficient granularity in the data used to be able to identify changes in an individual’s behavior at a required level, in addition this data is collected with insufficient context to be able to truly understand what the data represents. Where there are connections between learning analytics and student support these are related to student retention and academic performance. Although it has been identified that learning analytics can impact on student and staff behaviors, there is no evidence of staff and student wellbeing being considered in current policies or in the existing policy frameworks. The recommendation from the 2017 Stepchange framework has not been met and reviews of current practices need to be undertaken if learning analytics is to be part of Mentally Healthy Universities moving forward. In conclusion, although learning analytics is a growing field and becoming operationalized within United Kingdom Higher Education it is still in its reactive infancy. Current data models rely on proxies for student engagement and may not truly represent student behaviors. At this time there is inadequate sophistication for the use of learning analytics to identify student wellbeing concerns. However, as with all technologies, learning analytics is not benign, and changes to ways of working impact on both staff and students, wellbeing professionals should be included as key stakeholders in the development of learning analytics and student support policies and wellbeing considerations explicitly mentioned and taken into account. |
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title_short |
Making a #Stepchange? Investigating the Alignment of Learning Analytics and Student Wellbeing in United Kingdom Higher Education Institutions |
url |
https://doi.org/10.3389/feduc.2020.531424 https://doaj.org/article/3001bd307fc24fbfa7eb5e96e1f426fd https://www.frontiersin.org/articles/10.3389/feduc.2020.531424/full https://doaj.org/toc/2504-284X |
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up_date |
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