This document describes the development of an instrument called the Student Expectations of Learning Analytics Questionnaire (SELAQ) to measure students' expectations of learning analytics services. The researchers conducted a literature review on stakeholder engagement in learning analytics and identified gaps between managerial and student perspectives. They developed the SELAQ using a theoretical framework involving ethical, agency, intervention, and meaningfulness expectations. An initial 79-item version was reduced to 12 items through pilot testing and validation. The SELAQ is a valid tool to help institutions implement learning analytics in a way that aligns with students' expectations.
Schools, funding and performance: Lessons from the NSW National Partnerships. On November 18, Professor Stephen Lamb presented at a CESE Seminar on:
• Recent changes in school funding
• Evidence of impact of funding
• Evidence from evaluations of NSW low SES National Partnerships
• Conditions for ensuring success.
LEARNING ANALYTICS IN SCHOOLS
https://latte-analytics.sydney.edu.au/school/ for updates.
Date: Monday 5 March, 2018
Time: 8.30am—3.15pm
Venue: SMC Conference & Function Centre, 66 Goulburn Street, Sydney NSW 2000
In association with the 8th International Conference on Learning Analytics & Knowledge, Society for Learning Analytics Research
Briefing papers: https://latte-analytics.sydney.edu.au/wp-content/uploads/2017/10/k12_papers-1.pdf
You are warmly invited to join this inaugural event!
The data and analytics revolutions are disrupting and already transforming many sectors in society: finance, health, shopping, politics. Data is not new to education, but for many, it is still challenging to articulate the connection between the potential of using data to support decision making, and the every day-to-day operations occurring in learning environments.
School leaders, teachers, data analysts, academics, policy makers and all other interested parties are invited to join a professional learning and development day focused on the practical applications of Learning Analytics in school (K-12) education.
Drawing on national and international expertise, speakers include innovative school leaders and teachers, school data analysts, university researchers, government and software companies. Whether you already know a bit about Learning Analytics, are brand new to it, or already use it in the classroom, there will be insightful sessions with pertinent applications for all levels of knowledge and understanding.
You will leave with a deeper understanding of:
The diverse forms that Learning Analytics can take, and especially how technology extends this far beyond conventional school data to create better feedback
How such data is being used by school leaders to support strategic reflection
How new kinds of data are being used by teachers to support their practice
The practicalities of initiating such work in your own school
This is the first event of its kind in Australia, and a new initiative for the international LAK conference, so you will make many professional connections as we forge this new network.
Learning analytics is the measurement, collection, analysis and reporting of student data to understand and optimize the learning process. Visualization of data plays an important role in learning analytics by making patterns in the data clear. Examples discussed include tools that analyze data from sources like LMS systems and instructor grades to provide students and teachers insights. Both educational data mining and information visualization approaches were presented as ways to apply learning analytics. The role of teachers in learning analytics was also discussed.
Socialization and Inquiry Based Learning in Math to Improve Student SuccessTrishaReimer
This document outlines a plan to implement socialization and inquiry-based learning in a math program. It aims to increase student engagement, motivation, and learning through collaborative problem-solving and critical thinking activities. The initiative will create lessons integrating these methods and collect data on student outcomes before and after. If successful, it could be expanded district-wide.
Let’s get there! Towards policy for adoption of learning analyticsDragan Gasevic
1) The document discusses challenges in adopting learning analytics and proposes a policy framework to guide the process.
2) Key adoption challenges include developing leadership, engaging stakeholders, providing training in data literacy, and establishing policies.
3) The framework suggests mapping the political context, identifying stakeholders, desired behavior changes, and developing an engagement strategy. It also involves analyzing capacity and establishing monitoring frameworks.
4) The goal is to provide an inclusive adoption process that embraces the complexity of educational systems and promotes innovation.
Data visualisation with predictive learning analyticsChris Ballard
The document discusses using predictive analytics and data visualization in education. It outlines an objective to build predictive models for student success and map them to retention themes. Examples of visualization include monitoring courses and modules, and identifying at-risk students. Guidelines recommend visualizations be simple to interpret, adapt to the user, indicate how predictions are built, bridge predictive and historical data, enable user response and monitoring of actions. The goal is to identify at-risk students earlier and understand factors influencing student success.
What are the essential elements needed to provide effective and sustainable evidence-based programs for students with ASD across the age range? How can effective programs be replicated across a large system? Come learn how three states (Oregon, Arizona & Arkansas) have developed solutions for building their capacity to serve all students with autism. Specifically, the OrPATS Project (Oregon Regional Program Autism Training Sites), AzSECAP (Arizona Statewide Early Childhood Autism Project) and Easter Seals Connect Project will be discussed.
LEARNING ANALYTICS IN SCHOOLS
https://latte-analytics.sydney.edu.au/school/ for updates.
Date: Monday 5 March, 2018
Time: 8.30am—3.15pm
Venue: SMC Conference & Function Centre, 66 Goulburn Street, Sydney NSW 2000
In association with the 8th International Conference on Learning Analytics & Knowledge, Society for Learning Analytics Research
Briefing papers: https://latte-analytics.sydney.edu.au/wp-content/uploads/2017/10/k12_papers-1.pdf
You are warmly invited to join this inaugural event!
The data and analytics revolutions are disrupting and already transforming many sectors in society: finance, health, shopping, politics. Data is not new to education, but for many, it is still challenging to articulate the connection between the potential of using data to support decision making, and the every day-to-day operations occurring in learning environments.
School leaders, teachers, data analysts, academics, policy makers and all other interested parties are invited to join a professional learning and development day focused on the practical applications of Learning Analytics in school (K-12) education.
Drawing on national and international expertise, speakers include innovative school leaders and teachers, school data analysts, university researchers, government and software companies. Whether you already know a bit about Learning Analytics, are brand new to it, or already use it in the classroom, there will be insightful sessions with pertinent applications for all levels of knowledge and understanding.
You will leave with a deeper understanding of:
The diverse forms that Learning Analytics can take, and especially how technology extends this far beyond conventional school data to create better feedback
How such data is being used by school leaders to support strategic reflection
How new kinds of data are being used by teachers to support their practice
The practicalities of initiating such work in your own school
This is the first event of its kind in Australia, and a new initiative for the international LAK conference, so you will make many professional connections as we forge this new network.
Schools, funding and performance: Lessons from the NSW National Partnerships. On November 18, Professor Stephen Lamb presented at a CESE Seminar on:
• Recent changes in school funding
• Evidence of impact of funding
• Evidence from evaluations of NSW low SES National Partnerships
• Conditions for ensuring success.
LEARNING ANALYTICS IN SCHOOLS
https://latte-analytics.sydney.edu.au/school/ for updates.
Date: Monday 5 March, 2018
Time: 8.30am—3.15pm
Venue: SMC Conference & Function Centre, 66 Goulburn Street, Sydney NSW 2000
In association with the 8th International Conference on Learning Analytics & Knowledge, Society for Learning Analytics Research
Briefing papers: https://latte-analytics.sydney.edu.au/wp-content/uploads/2017/10/k12_papers-1.pdf
You are warmly invited to join this inaugural event!
The data and analytics revolutions are disrupting and already transforming many sectors in society: finance, health, shopping, politics. Data is not new to education, but for many, it is still challenging to articulate the connection between the potential of using data to support decision making, and the every day-to-day operations occurring in learning environments.
School leaders, teachers, data analysts, academics, policy makers and all other interested parties are invited to join a professional learning and development day focused on the practical applications of Learning Analytics in school (K-12) education.
Drawing on national and international expertise, speakers include innovative school leaders and teachers, school data analysts, university researchers, government and software companies. Whether you already know a bit about Learning Analytics, are brand new to it, or already use it in the classroom, there will be insightful sessions with pertinent applications for all levels of knowledge and understanding.
You will leave with a deeper understanding of:
The diverse forms that Learning Analytics can take, and especially how technology extends this far beyond conventional school data to create better feedback
How such data is being used by school leaders to support strategic reflection
How new kinds of data are being used by teachers to support their practice
The practicalities of initiating such work in your own school
This is the first event of its kind in Australia, and a new initiative for the international LAK conference, so you will make many professional connections as we forge this new network.
Learning analytics is the measurement, collection, analysis and reporting of student data to understand and optimize the learning process. Visualization of data plays an important role in learning analytics by making patterns in the data clear. Examples discussed include tools that analyze data from sources like LMS systems and instructor grades to provide students and teachers insights. Both educational data mining and information visualization approaches were presented as ways to apply learning analytics. The role of teachers in learning analytics was also discussed.
Socialization and Inquiry Based Learning in Math to Improve Student SuccessTrishaReimer
This document outlines a plan to implement socialization and inquiry-based learning in a math program. It aims to increase student engagement, motivation, and learning through collaborative problem-solving and critical thinking activities. The initiative will create lessons integrating these methods and collect data on student outcomes before and after. If successful, it could be expanded district-wide.
Let’s get there! Towards policy for adoption of learning analyticsDragan Gasevic
1) The document discusses challenges in adopting learning analytics and proposes a policy framework to guide the process.
2) Key adoption challenges include developing leadership, engaging stakeholders, providing training in data literacy, and establishing policies.
3) The framework suggests mapping the political context, identifying stakeholders, desired behavior changes, and developing an engagement strategy. It also involves analyzing capacity and establishing monitoring frameworks.
4) The goal is to provide an inclusive adoption process that embraces the complexity of educational systems and promotes innovation.
Data visualisation with predictive learning analyticsChris Ballard
The document discusses using predictive analytics and data visualization in education. It outlines an objective to build predictive models for student success and map them to retention themes. Examples of visualization include monitoring courses and modules, and identifying at-risk students. Guidelines recommend visualizations be simple to interpret, adapt to the user, indicate how predictions are built, bridge predictive and historical data, enable user response and monitoring of actions. The goal is to identify at-risk students earlier and understand factors influencing student success.
What are the essential elements needed to provide effective and sustainable evidence-based programs for students with ASD across the age range? How can effective programs be replicated across a large system? Come learn how three states (Oregon, Arizona & Arkansas) have developed solutions for building their capacity to serve all students with autism. Specifically, the OrPATS Project (Oregon Regional Program Autism Training Sites), AzSECAP (Arizona Statewide Early Childhood Autism Project) and Easter Seals Connect Project will be discussed.
LEARNING ANALYTICS IN SCHOOLS
https://latte-analytics.sydney.edu.au/school/ for updates.
Date: Monday 5 March, 2018
Time: 8.30am—3.15pm
Venue: SMC Conference & Function Centre, 66 Goulburn Street, Sydney NSW 2000
In association with the 8th International Conference on Learning Analytics & Knowledge, Society for Learning Analytics Research
Briefing papers: https://latte-analytics.sydney.edu.au/wp-content/uploads/2017/10/k12_papers-1.pdf
You are warmly invited to join this inaugural event!
The data and analytics revolutions are disrupting and already transforming many sectors in society: finance, health, shopping, politics. Data is not new to education, but for many, it is still challenging to articulate the connection between the potential of using data to support decision making, and the every day-to-day operations occurring in learning environments.
School leaders, teachers, data analysts, academics, policy makers and all other interested parties are invited to join a professional learning and development day focused on the practical applications of Learning Analytics in school (K-12) education.
Drawing on national and international expertise, speakers include innovative school leaders and teachers, school data analysts, university researchers, government and software companies. Whether you already know a bit about Learning Analytics, are brand new to it, or already use it in the classroom, there will be insightful sessions with pertinent applications for all levels of knowledge and understanding.
You will leave with a deeper understanding of:
The diverse forms that Learning Analytics can take, and especially how technology extends this far beyond conventional school data to create better feedback
How such data is being used by school leaders to support strategic reflection
How new kinds of data are being used by teachers to support their practice
The practicalities of initiating such work in your own school
This is the first event of its kind in Australia, and a new initiative for the international LAK conference, so you will make many professional connections as we forge this new network.
VII Jornadas eMadrid "Education in exponential times". "Supporting higher edu...eMadrid network
VII Jornadas eMadrid "Education in exponential times". "Supporting higher education in integrating learning analytics". Dragan Gasevic. U Edinburgh, UK. 05/07/2017.
This document discusses becoming an evidence-based SENCO and making evidence-based decisions. It provides an overview of effective SEN support and a definition of evidence-based practice. It addresses common misconceptions and highlights techniques for making evidence-based decisions, including asking well-formulated questions using the PICO format, acquiring evidence from various sources, appraising the quality of evidence, and aggregating evidence. It emphasizes acting on the evidence and assessing results through after-action reviews. The key message is that evidence-based practice is essential for SEND but also presents challenges that can be addressed through reasonably straightforward techniques.
Moving Forward on Learning Analytics - A/Professor Deborah West, Charles Darw...Blackboard APAC
Learning analytics is a 'hot topic' in education with many institutions seeking to make better use of the data available via various systems. One of the key challenges in this process is to understand the business questions that people working in various roles in institutions would like to be able to answer. However, it is also important that these questions are appropriately structured and specific in order to gather the relevant data. This session builds on the workshop run at last year's Blackboard Learning and Teaching conference where participants explored business questions and use cases for learning analytics from a range of perspectives.
Delivered at Innovate and Educate: Teaching and Learning Conference by Blackboard. 24 -27 August 2015 in Adelaide, Australia.
Graphic Calculators: An Impact on Mathematics Classroomsjrmyles1
This document discusses the impact of graphic calculators in mathematics classrooms. It explores whether paper and pencil or graphic calculators are better, finding that calculators are not preferable for simple calculations but can improve accuracy, pace, critical thinking, and help overcome difficulties for students. The document also notes advantages like building assurance, variety, appeal and peer exchange. It examines how teachers become facilitators and students become more motivated with higher-order thinking and exploration when using calculators. Potential impacts include building confidence in math, making connections to retain material better, and preparing students for high-stakes tests through conceptual explorations.
Australian university teacher’s engagement with learning analytics: Still ea...Blackboard APAC
This session reports the results of a recent OLT-funded national exploratory study addressing the relevant factors and their impact when implementing learning analytics for student retention purposes. The project utilised a mixed-method research design and yielded a series of outputs, including the development of a non-technical overview of learning analytics, focusing on linking the fields of student retention and learning analytics resulting in an institution level survey focusing on sector readiness and decision making relating to utilising learning analytics for retention purposes. An academic level survey was administered to academic staff exploring their progress, aspirations and support needs relating to learning analytics. Follow-up interviews expanded on their experiences with learning analytics to date. An evidence-based framework was developed, mapping important factors affecting learning analytics decision making and implementation. This was illustrated by a suite of five case studies developed by each of the research partner institutions detailing their experiences with learning analytics and demonstrating why elements in the framework are important. These findings were shared and tested at a National Forum in April 2015.
Delivered at Innovate and Educate: Teaching and Learning Conference by Blackboard. 24 -27 August 2015 in Adelaide, Australia.
Utilising action research and enquiry processes to achieve sustainable academ...Bettina Schwenger
1) The document discusses using action research and enquiry processes to achieve sustainable academic development for teaching staff through professional development programs.
2) It provides background on the New Zealand context and describes key components of successful change initiatives like addressing occupational identity and using reflection and evaluation.
3) The conclusion reflects on preliminary research findings that action research approaches can create common ground between participants and help make teachers more effective by focusing on student gains through their teaching.
Influence of Motivation to Learn on Training Satisfaction Kristin Petrunin
The document summarizes a presentation given at the SERA Conference 2015 about current trends in career and technical education (CTE). It discusses students, teachers, and administrators involved in CTE and how to help CTE teachers. The presentation reports on a study that found a moderate positive correlation between CTE teachers' motivation to learn and their satisfaction with training, suggesting ways to increase motivation at CTE professional development conferences.
This document outlines techniques for using student voices and data-driven decision making to improve schools. It discusses Photolanguage, an innovative process using black and white photos to stimulate reflection. Data-in-a-Day is also introduced, which involves collecting data from multiple stakeholders over the course of a day to facilitate dialogue about improvement strategies. Guidelines are provided for analyzing data to identify themes, determine program effectiveness, and guide decisions. The goal is for evaluators and schools to work collaboratively to understand challenges and make ongoing improvements based on consensus.
This document welcomes students to the University of Arizona College of Medicine and provides tips for success as a medical student. It emphasizes engagement, asking questions, supporting others, developing a growth mindset, reflecting on learning, and transitioning study skills. It outlines the curriculum, which includes distinction tracks and a scholarly project. It also discusses incorporating themes of health disparities, racism, and structural racism throughout the pre-clerkship and clerkship phases. Faculty are trained on bias and cultural competency is emphasized. Students are encouraged to reach out for support from administrators.
2009-01-14 STEM Ed in CPS to Donors Forum - draft 4Michael Lach
The document discusses strategies to improve mathematics and science education in K-12 schools. It outlines several initiatives, including developing instructional leadership teams, implementing instructional rounds to share best practices, and expanding extracurricular programs in STEM fields. It also notes that most school leaders do not see math and science education as a serious problem, and evaluates some strategies as only pilot programs rather than robust, research-backed approaches.
Social network analysis and learning designDragan Gasevic
This presentation is prepared for DALMOOC and talks about the use of social network analysis for improvement of learning design. The presentation is based on
Lockyer, L., Heathcote, E., & Dawson, S. (2013). Informing pedagogical action: Aligning learning analytics with learning design. American Behavioral Scientist, 57(10), 1439-1459, doi:10.1177/0002764213479367
The Creative Thinking - Science Exposure program in Israel is an innovative program to teach scientific concepts to very young children via fun activities and the creation of scientific toys.
Value added methodology measures student growth and can provide useful information to educators. It analyzes learning trajectories to target interventions and assess placement fairness. This helps meet all student needs. While standardized tests cause "shed patterns" of disproportionate gains, the goal is equal growth for all. Teacher effectiveness strongly influences academic growth. Principals should use value added data to match teachers' strengths to student needs, leading to improved schools.
The document describes a professional development program called Effective Interventions for Behaviour Challenges (EIBC) developed in New Zealand to improve services for children with challenging behaviors. The program used a blended learning model including block courses, case study discussions, and mentoring. Evaluations found improvements in case reports over time and high satisfaction ratings among participants, demonstrating the program was an effective approach for developing education consultants' skills. Critical factors for success included an evidence base, linking course content to real cases, and collaborative problem-solving through study groups.
This document discusses the EVAAS evaluation system for teachers and educator preparation programs in North Carolina. It provides an overview of how teacher effectiveness will be evaluated based on student growth and achievement data rather than solely on proficiency. Growth will be measured using EVAAS, which assesses the value added by a teacher in a given year. The document outlines the implications for exceptional children teachers, including how their standard 6 rating and effectiveness status will be calculated based on growth data. It also addresses how EVAAS data could factor into approvals for educator preparation programs at the campus and program level going forward.
Bb Tour ANZ 2017 - Predicting Student SuccessBlackboard APAC
This document discusses using predictive analytics to improve student retention and success. It summarizes a student success return on investment calculator showing how increasing retention rates from 95% to 96% could result in $6.78 million in additional revenue. It then provides an overview of Blackboard Predict, a predictive modeling tool that aggregates student data from learning management systems and student information systems to build models predicting things like the likelihood of earning a C or better or attending class. Sample predictive model outputs are shown, including feature importance and how the results could be distributed to instructors, students, and advisors to help intervene with at-risk students. A three month pilot implementation is proposed.
Response to intervention presentation 9 9-14 [autosaved]christopherhaskins
This document discusses Response to Intervention (RTI) and defines the five components of an RTI approach according to Hauerwas (2006). The five components are: 1) A problem-solving philosophy of collaborative inquiry, 2) A shared responsibility through an expanding circle of support, 3) A tiered intervention system, 4) Monitoring student progress through curriculum-based measurements, and 5) In some cases, RTI can be part of the special education process according to Rhode Island law. The presentation was given to Paul Cuffee School on 9/9/14 to discuss how they can implement the RTI framework.
Slide deck from the presentation for the workshop delivered at the Distance Teaching & Learning Conference in August 2016 at the University of Wisconsin-Madison. Facilitators representing Quality Matters were Kay Shattuck and Bethany Simunich.
07 18-13 webinar - sharnell jackson - using data to personalize learningDreamBox Learning
Learning and competency data can be useful tools in assessing a student’s individual learning needs. In this month’s Blended Learning webinar, presenters Sharnell Jackson and Tim Hudson shared best practices for organizing and using student data in order to better meet student needs. They also discussed processes for using and analyzing data at the student, classroom, and district levels.
VII Jornadas eMadrid "Education in exponential times". "Supporting higher edu...eMadrid network
VII Jornadas eMadrid "Education in exponential times". "Supporting higher education in integrating learning analytics". Dragan Gasevic. U Edinburgh, UK. 05/07/2017.
This document discusses becoming an evidence-based SENCO and making evidence-based decisions. It provides an overview of effective SEN support and a definition of evidence-based practice. It addresses common misconceptions and highlights techniques for making evidence-based decisions, including asking well-formulated questions using the PICO format, acquiring evidence from various sources, appraising the quality of evidence, and aggregating evidence. It emphasizes acting on the evidence and assessing results through after-action reviews. The key message is that evidence-based practice is essential for SEND but also presents challenges that can be addressed through reasonably straightforward techniques.
Moving Forward on Learning Analytics - A/Professor Deborah West, Charles Darw...Blackboard APAC
Learning analytics is a 'hot topic' in education with many institutions seeking to make better use of the data available via various systems. One of the key challenges in this process is to understand the business questions that people working in various roles in institutions would like to be able to answer. However, it is also important that these questions are appropriately structured and specific in order to gather the relevant data. This session builds on the workshop run at last year's Blackboard Learning and Teaching conference where participants explored business questions and use cases for learning analytics from a range of perspectives.
Delivered at Innovate and Educate: Teaching and Learning Conference by Blackboard. 24 -27 August 2015 in Adelaide, Australia.
Graphic Calculators: An Impact on Mathematics Classroomsjrmyles1
This document discusses the impact of graphic calculators in mathematics classrooms. It explores whether paper and pencil or graphic calculators are better, finding that calculators are not preferable for simple calculations but can improve accuracy, pace, critical thinking, and help overcome difficulties for students. The document also notes advantages like building assurance, variety, appeal and peer exchange. It examines how teachers become facilitators and students become more motivated with higher-order thinking and exploration when using calculators. Potential impacts include building confidence in math, making connections to retain material better, and preparing students for high-stakes tests through conceptual explorations.
Australian university teacher’s engagement with learning analytics: Still ea...Blackboard APAC
This session reports the results of a recent OLT-funded national exploratory study addressing the relevant factors and their impact when implementing learning analytics for student retention purposes. The project utilised a mixed-method research design and yielded a series of outputs, including the development of a non-technical overview of learning analytics, focusing on linking the fields of student retention and learning analytics resulting in an institution level survey focusing on sector readiness and decision making relating to utilising learning analytics for retention purposes. An academic level survey was administered to academic staff exploring their progress, aspirations and support needs relating to learning analytics. Follow-up interviews expanded on their experiences with learning analytics to date. An evidence-based framework was developed, mapping important factors affecting learning analytics decision making and implementation. This was illustrated by a suite of five case studies developed by each of the research partner institutions detailing their experiences with learning analytics and demonstrating why elements in the framework are important. These findings were shared and tested at a National Forum in April 2015.
Delivered at Innovate and Educate: Teaching and Learning Conference by Blackboard. 24 -27 August 2015 in Adelaide, Australia.
Utilising action research and enquiry processes to achieve sustainable academ...Bettina Schwenger
1) The document discusses using action research and enquiry processes to achieve sustainable academic development for teaching staff through professional development programs.
2) It provides background on the New Zealand context and describes key components of successful change initiatives like addressing occupational identity and using reflection and evaluation.
3) The conclusion reflects on preliminary research findings that action research approaches can create common ground between participants and help make teachers more effective by focusing on student gains through their teaching.
Influence of Motivation to Learn on Training Satisfaction Kristin Petrunin
The document summarizes a presentation given at the SERA Conference 2015 about current trends in career and technical education (CTE). It discusses students, teachers, and administrators involved in CTE and how to help CTE teachers. The presentation reports on a study that found a moderate positive correlation between CTE teachers' motivation to learn and their satisfaction with training, suggesting ways to increase motivation at CTE professional development conferences.
This document outlines techniques for using student voices and data-driven decision making to improve schools. It discusses Photolanguage, an innovative process using black and white photos to stimulate reflection. Data-in-a-Day is also introduced, which involves collecting data from multiple stakeholders over the course of a day to facilitate dialogue about improvement strategies. Guidelines are provided for analyzing data to identify themes, determine program effectiveness, and guide decisions. The goal is for evaluators and schools to work collaboratively to understand challenges and make ongoing improvements based on consensus.
This document welcomes students to the University of Arizona College of Medicine and provides tips for success as a medical student. It emphasizes engagement, asking questions, supporting others, developing a growth mindset, reflecting on learning, and transitioning study skills. It outlines the curriculum, which includes distinction tracks and a scholarly project. It also discusses incorporating themes of health disparities, racism, and structural racism throughout the pre-clerkship and clerkship phases. Faculty are trained on bias and cultural competency is emphasized. Students are encouraged to reach out for support from administrators.
2009-01-14 STEM Ed in CPS to Donors Forum - draft 4Michael Lach
The document discusses strategies to improve mathematics and science education in K-12 schools. It outlines several initiatives, including developing instructional leadership teams, implementing instructional rounds to share best practices, and expanding extracurricular programs in STEM fields. It also notes that most school leaders do not see math and science education as a serious problem, and evaluates some strategies as only pilot programs rather than robust, research-backed approaches.
Social network analysis and learning designDragan Gasevic
This presentation is prepared for DALMOOC and talks about the use of social network analysis for improvement of learning design. The presentation is based on
Lockyer, L., Heathcote, E., & Dawson, S. (2013). Informing pedagogical action: Aligning learning analytics with learning design. American Behavioral Scientist, 57(10), 1439-1459, doi:10.1177/0002764213479367
The Creative Thinking - Science Exposure program in Israel is an innovative program to teach scientific concepts to very young children via fun activities and the creation of scientific toys.
Value added methodology measures student growth and can provide useful information to educators. It analyzes learning trajectories to target interventions and assess placement fairness. This helps meet all student needs. While standardized tests cause "shed patterns" of disproportionate gains, the goal is equal growth for all. Teacher effectiveness strongly influences academic growth. Principals should use value added data to match teachers' strengths to student needs, leading to improved schools.
The document describes a professional development program called Effective Interventions for Behaviour Challenges (EIBC) developed in New Zealand to improve services for children with challenging behaviors. The program used a blended learning model including block courses, case study discussions, and mentoring. Evaluations found improvements in case reports over time and high satisfaction ratings among participants, demonstrating the program was an effective approach for developing education consultants' skills. Critical factors for success included an evidence base, linking course content to real cases, and collaborative problem-solving through study groups.
This document discusses the EVAAS evaluation system for teachers and educator preparation programs in North Carolina. It provides an overview of how teacher effectiveness will be evaluated based on student growth and achievement data rather than solely on proficiency. Growth will be measured using EVAAS, which assesses the value added by a teacher in a given year. The document outlines the implications for exceptional children teachers, including how their standard 6 rating and effectiveness status will be calculated based on growth data. It also addresses how EVAAS data could factor into approvals for educator preparation programs at the campus and program level going forward.
Bb Tour ANZ 2017 - Predicting Student SuccessBlackboard APAC
This document discusses using predictive analytics to improve student retention and success. It summarizes a student success return on investment calculator showing how increasing retention rates from 95% to 96% could result in $6.78 million in additional revenue. It then provides an overview of Blackboard Predict, a predictive modeling tool that aggregates student data from learning management systems and student information systems to build models predicting things like the likelihood of earning a C or better or attending class. Sample predictive model outputs are shown, including feature importance and how the results could be distributed to instructors, students, and advisors to help intervene with at-risk students. A three month pilot implementation is proposed.
Response to intervention presentation 9 9-14 [autosaved]christopherhaskins
This document discusses Response to Intervention (RTI) and defines the five components of an RTI approach according to Hauerwas (2006). The five components are: 1) A problem-solving philosophy of collaborative inquiry, 2) A shared responsibility through an expanding circle of support, 3) A tiered intervention system, 4) Monitoring student progress through curriculum-based measurements, and 5) In some cases, RTI can be part of the special education process according to Rhode Island law. The presentation was given to Paul Cuffee School on 9/9/14 to discuss how they can implement the RTI framework.
Slide deck from the presentation for the workshop delivered at the Distance Teaching & Learning Conference in August 2016 at the University of Wisconsin-Madison. Facilitators representing Quality Matters were Kay Shattuck and Bethany Simunich.
07 18-13 webinar - sharnell jackson - using data to personalize learningDreamBox Learning
Learning and competency data can be useful tools in assessing a student’s individual learning needs. In this month’s Blended Learning webinar, presenters Sharnell Jackson and Tim Hudson shared best practices for organizing and using student data in order to better meet student needs. They also discussed processes for using and analyzing data at the student, classroom, and district levels.
This document outlines the development of an instrument to measure student expectations of quality in learning analytics services. The authors aimed to highlight the importance of service quality and develop a tool to explore what students expect from learning analytics. They created survey items based on themes from prior literature, conducted a pilot study, and refined the instrument using exploratory factor analysis. The resulting survey measures student expectations across two factors: service expectations and ethical expectations. Future work will involve developing a perceptions scale and modeling student intentions to use learning analytics.
Talk by Rebeca Ferguson (Open University, UK, and LACE project).
The promise of learning analytics is that they will enable us to understand and optimize learning and the environments in which it takes place. The intention is to develop models, algorithms, and processes that can be widely used. In order to do this, we need to move from small-scale research within our disciplines towards large-scale implementation across our institutions. This is a tough challenge, because educational institutions are stable systems, resistant to change. To avoid failure and maximize success, implementation of learning analytics at scale requires careful consideration of the entire ‘TEL technology complex’. This complex includes the different groups of people involved, the educational beliefs and practices of those groups, the technologies they use, and the specific environments within which they operate. Providing reliable and trustworthy analytics is just one part of implementing analytics at scale. It is also important to develop a clear strategic vision, assess institutional culture critically, identify potential barriers to adoption, develop approaches that can overcome these, and put in place appropriate forms of support, training, and community building. In her keynote, Rebecca introduced tools, resources, organisations and case studies that can be used to support the deployment of learning analytics at scale
OIE Project Director's Meeting 2021 - Remote Teaching and Online Learning in ...Michael Barbour
Barbour, M. K. (2021, April). Remote teaching and online learning in an emergency: Understanding pandemic pedagogy [Keynote]. Our History. Our Story. Our Way: Office of Indian Education Project Director’s Meeting.
Moving Beyond Student Ratings to Evaluate TeachingVicki L. Wise
Evidence of teaching quality needs to take into account multiple sources, as teaching is multidimensional. Moreover, the likelihood of obtaining reliable and valid data and making appropriate judgments are increased with more evidence.
The document summarizes a case study on using data analysis and learning analytics in higher education. It describes how data was collected through student surveys to understand attitudes towards university services quality. The data was analyzed using SPSS and most students had positive attitudes. Recommendations included using additional quality models and awareness campaigns for services. Data scientists can help universities make data-driven decisions to improve student outcomes and resource allocation.
The document discusses the challenges of designing effective learner dashboards. It notes the potential benefits of learning analytics for improving understanding of learning and student outcomes. Learner dashboards present data on student learning behaviors but determining what information is useful can be difficult. Students' responses to dashboards varied - some found comparative data motivating while others found it demotivating. Effective dashboards should allow customization, provide actionable insights, and support the student-tutor relationship. How data is presented and how dashboards are integrated into the learning process are important considerations for realizing their benefits.
Learning analytics research informed institutional practiceYi-Shan Tsai
The document summarizes learning analytics research and initiatives at the University of Edinburgh. It discusses early MOOC and VLE analytics projects that aimed to understand student behaviors and identify patterns. It also describes the Learning Analytics Map of Activities, Research and Roll-out (LAMARR) and efforts to build institutional capacity for learning analytics. Challenges discussed include the effort required to analyze raw data and involve stakeholders. The document advocates developing critical and participatory approaches to educational data analysis.
This document provides several reasons why assessment is important for colleges and accreditation. It discusses the need to clearly articulate learning outcomes, demonstrate that students are achieving outcomes, test graduating students, and show how student outcome data leads to improved learning. The key reasons given are that assessment is needed for accreditation, to prove education quality to stakeholders, and address past feedback that called for more meaningful student learning data and assessment of curriculum effectiveness.
C:\Documents And Settings\Avoorhees\Desktop\A S S E S S M ES T
This document provides several reasons why assessment is important for colleges and accreditation. It discusses the need to clearly articulate learning outcomes, demonstrate that students are achieving outcomes, test graduating students, and show how student outcome data leads to improved learning. The key reasons given are that assessment is needed for accreditation, to prove education quality to stakeholders, and address past feedback that called for more meaningful student learning data and assessment of curriculum effectiveness.
Feedback, Agency and Analytics in Virtual Learning Environments – Creating a ...Diogo Casanova
The project comprises of a review of the literature and current technical provision of assessment and feedback in Virtual Learning Environments (VLEs); and data collected from ‘Sandpits’ with students and lecturers in two HEIs in the UK. A ‘Sandpit’ is a type of creative design-thinking focus group where participants are stimulated by a narrative of a scenario around the use of a product, object or artefact and are encouraged to critique, discuss and re-design it (Frohlich, Lim and Ahmed, 2014; Casanova and Mitchell, 2017). These ‘Sandpits’ look to clarify the role of VLEs in assessment and feedback, through understanding students’ perceptions of feedback and how they are being addressed and understanding teachers’ perceptions of the constraints they face. We are exploring what is available, looking to improve interface designs and features, and present these to VLE product designers.
This document discusses how analytics can be used to improve student success. It begins by describing a session that shows how analytics identify opportunities to improve student success. Participants will learn how to connect predictions of risk to interventions most likely to work under different conditions. The document then discusses how data is changing education and how analytics can be applied in areas like enrollment management, student services, and program design. It provides examples of how predictive analytics have been used at various institutions to improve retention, successful course completion, and graduation rates. The document emphasizes linking predictions of risk to specific interventions and measuring the impact and ROI of different interventions.
Assessing OER impact across varied organisations and learners: experiences fr...Beck Pitt
This presentation was co-authored by Tim Coughlan (Nottingham), Beck Pitt (OU), Patrick McAndrew (OU) and Nassim Ebrahimi (Anne Arundel).
It was presented at OER13, Nottingham, UK which took place 26-27 March 2013.
Assessing OER impact across varied organisations and learners: experiences fr...OER Hub
This presentation was co-authored by Tim Coughlan (Nottingham), Beck Pitt (OU), Patrick McAndrew (OU) and Nassim Ebrahimi (Anne Arundel).
It was presented at OER13, Nottingham, UK which took place 26-27 March 2013.
Similar to Students’ Expectations of Learning Analytics (20)
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
Assessment and Planning in Educational technology.pptxKavitha Krishnan
In an education system, it is understood that assessment is only for the students, but on the other hand, the Assessment of teachers is also an important aspect of the education system that ensures teachers are providing high-quality instruction to students. The assessment process can be used to provide feedback and support for professional development, to inform decisions about teacher retention or promotion, or to evaluate teacher effectiveness for accountability purposes.
How to Manage Your Lost Opportunities in Odoo 17 CRMCeline George
Odoo 17 CRM allows us to track why we lose sales opportunities with "Lost Reasons." This helps analyze our sales process and identify areas for improvement. Here's how to configure lost reasons in Odoo 17 CRM
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
1. Students’ Expectations of
Learning Analytics
Alexander Whitelock-Wainwright, Dragan Gašević, and Ricardo Tejeiro
A.Wainwright@Liverpool.ac.uk
2. Aims
• Highlight the importance of stakeholder perspectives in learning
analytics services.
• Develop an instrument to measure students’ expectations of learning
analytics services.
3. Stakeholder Engagement
• Early engagement of stakeholders reduces likelihood of service
dissatisfaction (Brown, Venkatesh, and Goyal, 2014).
• Stakeholders should be engaged in learning analytics service
implementations (Ferguson, Macfadyen, Clow, Tynan, Alexander, and
Dawson, 2014).
• Limited instances of engagement (Tsai and Gašević, 2017).
4. Ideological Gap
• Learning analytics policies driven by managerial beliefs (Sclater,
2016).
• Not necessarily reflective of what students would expect.
• Discrepancies between beliefs (Ng and Forbes, 2009).
5. Student Beliefs
• Non-validated psychometric instrument (Arnold and Sclater, 2017).
• Dashboard features (Schumacher and Ifenthaler, 2017).
6. Instrument Development
• Student expectations of learning analytics services.
• Theoretical framework of expectations.
• Identified themes:
• Ethical and Privacy Expectations
• Agency Expectations
• Intervention Expectations
• Meaningfulness Expectations
7. Expectations
• Important feature of human cognition (Roese and Sherman, 2007).
• Framed as beliefs about the future (Olson and Dover, 1976).
• Ideal and predicted expectations (Thompson and Suñol, 1995).
8. Ethical and Privacy Expectations
• Students must be fully informed (Drachsler and Greller, 2016).
• Consent (Prinsloo and Slade, 2015; Sclater, 2016).
• Student perspectives (Slade and Prinsloo, 2014).
9. Agency Expectations
• Learning analytics to improve student support (Prinsloo and Slade,
2017).
• Students are agents in their own learning (Winne and Hadwin, 2012).
• Student-centred learning analytics (Kruse and Pongsajapan, 2012).
10. Intervention Expectations
• Identify at-risk students (Campbell, DeBlois, and Oblinger, 2007).
• Improve the student-teacher relationship (Liu, Bartimote-Aufflick,
Pardo, and Bridgeman, 2017).
• Dashboard expectations (Schumacher and Ifenthaler, 2017).
12. Instrument Development
• Initially created 79 items.
• Reduced to 37 items through peer review.
• Pilot test with 210 respondents (University of Edinburgh).
• 19 items retained and re-worded.
• Further roll-out with 674 respondents (University of Edinburgh).
• 12 item Student Expectations of Learning Analytics Questionnaire (SELAQ).
14. Model Validity
• 191 respondents from the University of Liverpool.
• Confirmatory Factor Analysis.
• MIMIC modelling – differential item functioning (Muthén, 1989).
The aims of our talk are to…
Highlight the importance of stakeholder perspectives in learning analytics services…
And to outline the development and validation of an instrument designed to explore student expectations of learning analytics services…
Taking what we know from information systems research… the inclusion of stakeholders in the design and implementation stages of a service… does reduce the likelihood of future dissatisfaction… as the service is reflective of what the stakeholders actually want…
In terms of learning analytics… researchers have called for higher education institutes to allow stakeholders to be involved with learning analytics service implementations…
But findings do suggest that the level of engagement from stakeholders… in learning analytics implementations has been low…
A notable example of limited student engagement has been the development of learning analytics policies… which tend to be led by what managers… researchers… and practitioners believe students want…
It is reasonable to assume that the intentions behind such policies are to improve learning performance… or to provide additional support…
Nevertheless… these may not be reflective of what students want from learning analytics…
The creation of a service which is not representative of student expectations… is an example of an ideological gap… which is a main cause of dissatisfaction…
To offset the possibility of creating an ideological gap… there is a need to explore student beliefs towards learning analytics services…
In the case of Arnold and Sclater… they sought to explore student attitudes toward the analysis and handling of educational data… the main issue here… and it has been highlighted by the authors… is that the instrument used has not been validated so their findings are questionable…
Schumacher has explored student expectations of dashboard features… this is an important step… but learning analytics is not predicated on the inclusion of this one tool… there are many aspects of learning analytics services…
Despite the issues mentioned… these examples present important steps in enabling students to have a say in learning analytics service developments…
Given the limitations of previous work… we sought to develop an instrument to explore student expectations of learning analytics services…
For the next few slides… I will…
Present the theoretical foundation on which the instrument is based on…
Then… I will discuss the four themes identified in the learning analytics literature… which guided the development of the questionnaire items…
Expectations are a fundamental part of human cognition… they influence motivation… and even the judgements we form…
They are also not too dissimilar from beliefs… where beliefs refer to a probability judgement between an object and an attribute… expectations are only discernible by the point in time on which this judgement is made…
In other words… expectations are framed as beliefs about the future…
But… the term expectation is general and does not allow for different types or levels of expectations…
Thompson… therefore… decomposed expectations into ideal and predicted… which refer to what individuals hope for… and what individuals believe they are most likely to receive…
Conceptualising expectations in this way will enable researchers to gain a better understanding of what students may desire from a learning analytics service… and also what they expect as minimum… thus through the use of segmentation procedures we can understand what features are most important to students…
There is a lot of literature in learning analytics that has discussed ethical and privacy issues…
In particular… the DELICATE checklist provides a series of advisory points to guide learning analytics implementations… one of which is to inform students about the procedures being undertaken… whether this is the type of data collected… the analyses carried out… or even how the findings will be used…
This then connects to the next point of consent… there has been debate concerning the extent to which students should consent to all components of learning analytics… or aspects such as interventions…
Even within this literature… these decisions are being made by researchers and practitioners… as opposed to asking students what they expect…
A good example of engaging students in this debate is presented by Slade… who found students to want universities to obtain consent before undertaking any learning analytics processes…
Together… this literature identifies a series of points that requires the input from students
Agency expectations refers to learning analytics services not creating a culture of passivity in higher education…
At the end of the day… students are responsible for their own learning… they are active agents who set their own goals and strategies… it is not for learning analytics to remove the ability of students to make their own decisions…
There are occasions where institutions may offer additional support… such as providing regular updates on how students are progressing towards particular goals… but we should always be mindful of whether students expect to make their own decisions based on the analyses provided…
Learning analytics has previously been dominated with research attempting to identify at-risk students… which then leads to the implementation of early interventions that should deter students from dropping out… although research findings have said this is usually not the case…
Beyond merely predicting dropouts… learning analytics has moved onto improving other aspects of education… for example… trying to improve student-teacher relationships by enabling tutors to better understand how students are performing and whether issues are present…
As with agency expectations… researchers are making inferences about the type of service students would like to receive in exchange for the disclosure of personal information… we don’t know what type of services students want…
There has been progress with the investigation in dashboard feature expectations… but more work is need
Meaningfulness expectations refers to the feedback from learning analytics services… being relevant to students… in order to promote a positive change such as motivating learning…
As with information systems… perceptions of usefulness are intrinsic to its acceptance…
If the feedback provided through learning analytics services is not pedagogically meaningful to students then they will not use it…
Therefore… we have included this theme to cover student beliefs about the applicability and relevance of learning analytics feedback to their learning…
Using the identified themes… we created 79 items that were subjected to peer review…
This process led to 37 items… which were used in a pilot study of the instrument at the University of Edinburgh…
210 students completed the questionnaire and provided qualitative feedback on each item…
The results were then analysed using factor analysis… which left 19 items… the qualitative feedback also identified some issues with the wording so additional changes were made…
These 19 items were then used in a final roll-out to all students at the University of Edinburgh…
We received 674 responses… which we again analysed using factor analysis…
This analysis did identify problems with certain items… such as cross-loadings and multicollinearity problems… these were removed which left us with the final 12 item student expectations of learning analytics questionnaire…
The final 12 items can be explained by a two-factor solution… these factors are ethical and service expectations…
And these factors are applicable to both the ideal and predicted subscales…
The 12-item instrument was then distributed to students at the University of Liverpool…
191 responses were collected…
The results for both scales show that the two-factor structure has an adequate fit… which strengthens the validity of the instrument.
Although the purported factor structure does have an adequate fit… it is important to understand whether the instrument is invariant across sub-groups…
Up until now… there has been no research exploring student perspectives of learning analytics across various subgroups… such as gender… or faculties…
The use of MIMIC modelling… or multiple indicator multiple cause modelling… allows researchers to explore whether there is differential item functioning within a instrument through the addition of direct effects of covariates on factor scores… and items of interest…
So we may find that the female students have higher ethical expectations overall…
This approach is important… as it can be used to overcome the limitation of researchers assuming that all student groups hold the same expectations toward learning analytics services…
Rather… we can start to tailor policy decisions to meet the needs of various sub-groups…
Therefore… for those who may want to use this instrument… the use of MIMIC modelling can enable a greater understand of whether expectations of learning analytics are invariant across groups or not…
The next steps in the project are to assess the reliability and validity of the instrument cross-culturally…
So… to achieve this we have distributed the questionnaire at Tallinn and the netherlands…
We are still waiting to run the survey in madrid…
From this data collection we will be able to assess whether expectations change across different institutions… it will also enable a greater number of universities to utilise this tool for their implementation of learning analytics…