Presentation from the April 2012 Independent Curriculum Group conference, "New Directions in Assessment." A quick overview of new assessments and some novel ways to use conventional assessments, based on work by Doug Lyons and Andrew Niblock.
Learning Analytics is an emerging topic of interest throughout all levels of education focusing on how to harness the power of data mining, interpretation, and modeling.
However, there are several similar terms (academic analytics, predictive analytics, business intelligence, etc.) that can confuse educators and administrators alike. In this session, we will unpack this new area of interest and discuss how institutions can begin to leverage available products and open source communities to utilize analytics to improve understandings of teaching and learning and to tailor education more effectively.
We will briefly present an overview of the learning analytics field, drawing from popular examples such as the Signals project at Purdue U. and the Check My Activity tool at U. Maryland, Baltimore County. We will also review the structure of Sakai CLE and OAE user-level metrics and briefly discuss projects to design and implement tools to utilize these metrics in meaningful ways.
Learnline - Early Warning System & Performance Dashboardgnivri1666
This document discusses using an early warning system (EWS) and performance dashboard to monitor online students and identify those falling behind or at risk of failure. It provides examples of how these tools can track student progress through learning materials and assessments. Notifications are then sent to students through the EWS to engage with them if they have low scores, missed deadlines, or are not adequately progressing through the course content. These tools help address issues like disconnection from students and inability to provide traditional feedback in online environments.
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.
[Extended] Bottom-up growth of learning analytics at two Australian universit...Danny Liu
Presented at the University of New South Wales Learning Analytics and Educational Data Science research group meeting, April 2016.
This presentation will outline two approaches to learning analytics at the University of Sydney and Macquarie University, where staff are closely involved in the coevolution and development of two bespoke learning analytics tools to personalise student-staff interactions at scale. The University of Sydney system, called the Student Relationship Engagement System (SRES), is a highly-customisable web-based tool that supports the efficient capture and collation of student datasets. A companion mobile app helps staff quickly collect and access student data. Through an embedded messaging system, teaching staff can set up fully customisable rules to contact students via personalised emails and text messages. A nascent feature allows staff to leverage machine learning to uncover hidden patterns and relationships within and between datasets. The Macquarie University system is an enhancement of an existing Moodle plug-in, the Moodle Engagement Analytics Plugin (MEAP). MEAP can readily access data on student assessments, completions, login activity, forum activity, and the gradebook, amongst others, which are customisably represented as ‘risk indicators’. MEAP allows flexible and customisable interrogation of these data, and provides staff the ability to send personalised emails to students based on these risk indicators. At both institutions, these learning analytics approaches have grown from the grassroots to address pressing staff needs, highlighting the importance of this bespoke coevolution process of design, development, and implementation. The systems have enjoyed substantial organic adoption and are associated with positive student outcomes. As open source developments, we are very interested in working together to open up accessible learning analytics to teachers and students.
Peter Gow is an educator, author, and speaker who has spent over 38 years working in independent schools. His life's work is helping independent schools deliver the best possible educational experience based on their mission. He does this through writing, speaking at conferences, and advising schools on issues like curriculum, assessment, professional development, and school culture. In his free time, he enjoys writing, maritime life, technology, and finding ways to improve education.
Two experienced independent school middle managers share lessons on making change that sticks while minimizing conflict and resistance. From NAIS Annual Conference, 2011.
Some basic principles of school leadership in our time, as gleaned from research done in the spring and summer of 2009 for the National Association of Independent Schools.
Presented as part of the "Leading Toward a Sustainable Future" workshop at the NAIS 2010 annual conference.
How schools can work with and for teachers to optimize environments for teaching and learning. PPT from 1-hour session at the 2010 National Association of Independent Schools Annual Conference titled "The Intentional Teacher: Better Teaching Through School-Teacher Dialogue." Supplementary resources include the book THE INTENTIONAL TEACHER: FORGING A GREAT CAREER IN THE INDEPENDENT SCHOOL CLASSROOM by Peter Gow (Avocus, 2009)
Learning Analytics is an emerging topic of interest throughout all levels of education focusing on how to harness the power of data mining, interpretation, and modeling.
However, there are several similar terms (academic analytics, predictive analytics, business intelligence, etc.) that can confuse educators and administrators alike. In this session, we will unpack this new area of interest and discuss how institutions can begin to leverage available products and open source communities to utilize analytics to improve understandings of teaching and learning and to tailor education more effectively.
We will briefly present an overview of the learning analytics field, drawing from popular examples such as the Signals project at Purdue U. and the Check My Activity tool at U. Maryland, Baltimore County. We will also review the structure of Sakai CLE and OAE user-level metrics and briefly discuss projects to design and implement tools to utilize these metrics in meaningful ways.
Learnline - Early Warning System & Performance Dashboardgnivri1666
This document discusses using an early warning system (EWS) and performance dashboard to monitor online students and identify those falling behind or at risk of failure. It provides examples of how these tools can track student progress through learning materials and assessments. Notifications are then sent to students through the EWS to engage with them if they have low scores, missed deadlines, or are not adequately progressing through the course content. These tools help address issues like disconnection from students and inability to provide traditional feedback in online environments.
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.
[Extended] Bottom-up growth of learning analytics at two Australian universit...Danny Liu
Presented at the University of New South Wales Learning Analytics and Educational Data Science research group meeting, April 2016.
This presentation will outline two approaches to learning analytics at the University of Sydney and Macquarie University, where staff are closely involved in the coevolution and development of two bespoke learning analytics tools to personalise student-staff interactions at scale. The University of Sydney system, called the Student Relationship Engagement System (SRES), is a highly-customisable web-based tool that supports the efficient capture and collation of student datasets. A companion mobile app helps staff quickly collect and access student data. Through an embedded messaging system, teaching staff can set up fully customisable rules to contact students via personalised emails and text messages. A nascent feature allows staff to leverage machine learning to uncover hidden patterns and relationships within and between datasets. The Macquarie University system is an enhancement of an existing Moodle plug-in, the Moodle Engagement Analytics Plugin (MEAP). MEAP can readily access data on student assessments, completions, login activity, forum activity, and the gradebook, amongst others, which are customisably represented as ‘risk indicators’. MEAP allows flexible and customisable interrogation of these data, and provides staff the ability to send personalised emails to students based on these risk indicators. At both institutions, these learning analytics approaches have grown from the grassroots to address pressing staff needs, highlighting the importance of this bespoke coevolution process of design, development, and implementation. The systems have enjoyed substantial organic adoption and are associated with positive student outcomes. As open source developments, we are very interested in working together to open up accessible learning analytics to teachers and students.
Peter Gow is an educator, author, and speaker who has spent over 38 years working in independent schools. His life's work is helping independent schools deliver the best possible educational experience based on their mission. He does this through writing, speaking at conferences, and advising schools on issues like curriculum, assessment, professional development, and school culture. In his free time, he enjoys writing, maritime life, technology, and finding ways to improve education.
Two experienced independent school middle managers share lessons on making change that sticks while minimizing conflict and resistance. From NAIS Annual Conference, 2011.
Some basic principles of school leadership in our time, as gleaned from research done in the spring and summer of 2009 for the National Association of Independent Schools.
Presented as part of the "Leading Toward a Sustainable Future" workshop at the NAIS 2010 annual conference.
How schools can work with and for teachers to optimize environments for teaching and learning. PPT from 1-hour session at the 2010 National Association of Independent Schools Annual Conference titled "The Intentional Teacher: Better Teaching Through School-Teacher Dialogue." Supplementary resources include the book THE INTENTIONAL TEACHER: FORGING A GREAT CAREER IN THE INDEPENDENT SCHOOL CLASSROOM by Peter Gow (Avocus, 2009)
Confronting Reality with Big Data & Learning Analytics
We are experiencing an explosion in the quantity of data available online from archives and live streams. Learning Analytics is concerned with how educational research, and learning platform design, can make more effective use of such data (Long & Siemens, 2011). Improving outcomes through the analysis of data is of interest to researchers, administrators, systems architects, social media developers, educators and learners. Analytics are being held up by some as a way to confront, and tackle, the tough new realities of less money, less attention, and higher accountability for quality of learning.
Researchers and vendors are building reporting capabilities into tools that provide unprecedented levels of data on learners. This symposium will show what is possible, and what's coming soon. What objections could possibly be raised to such progress?
However, information infrastructure embodies and shapes worldviews: classification schemes are not only systematic ways to capture and preserve, but also to forget, by virtue of what remains invisible (Bowker & Star, 1999). Learning analytics and recommendation engines are designed with a particular conception of ‘success’, driving the patterns deemed to be evidence of progress, the interventions that are deemed appropriate, the data captured and the rules that fire in software.
This symposium will air some of the critical arguments around the limits of decontextualised data and automated analytics, which often appear reductionist in nature, failing to illuminate higher order learning. There are complex ethical issues around data fusion, and it is not clear to what extent learners are empowered, in contrast to being merely the objects of tracking technology. Educators may also find themselves at the receiving end of a new battery of institutional ‘performance indicators’ that do not reflect what they consider to be authentic learning and teaching.
This Symposium will provide the opportunity to hear a series of brief presentations introducing contrasting perspectives, before the debate is opened to all. Speakers from a cross-section of The Open University will describe how we are connecting datasets, analysing student data and prototyping next generation analytics. Complementing this, JISC will present a national capability perspective, with an update on the JISC CETIS ‘landscape analysis’ of the field, which will clarify potential benefits, issues to consider, and help institutions to assess their current capability and possible next steps.
Participants will catch up with developments in this fast moving field, through exposure to the possibilities of analytics, as well as issues to be alert to.
1) The document discusses social learning analytics, which examines how learners interact and engage in social learning networks, discourses, and contexts.
2) It presents a taxonomy of social learning analytics, including social network analysis, discourse analysis, content analysis, analysis of learning dispositions, and analysis of social learning contexts.
3) The discussion emphasizes that social learning analytics should not just track what learners do, but also how the data is used to provide formative feedback and help learners grow, moving beyond just institutional tracking of students.
This document summarizes the Assessment of Higher Education Learning Outcomes (AHELO) feasibility study being conducted by the OECD. The study aims to assess learning outcomes in higher education on an international scale using measures that are valid across cultures and institutions. It will test the feasibility of reliably measuring generic skills as well as discipline-specific competencies in economics and engineering. The study involves developing assessment instruments, implementing them in a small pilot test involving multiple countries, and collecting contextual data about institutions and students. The goal is to provide a proof of concept for assessing higher education quality through learning outcomes while respecting institutional diversity.
Designing useful evaluations - An online workshop for the Jisc AF programme_I...Rachel Harris
This document summarizes a workshop on designing useful evaluations for projects funded by the JISC and Becta Curriculum Delivery Programme. The workshop covered the evaluation cycle, identifying intended outcomes and impact, determining what to evaluate, developing evaluation questions, and methods for undertaking evaluations. Examples of evaluation approaches used by different projects were discussed, including action research, external evaluators, and using both qualitative and quantitative data sources. Participants were guided in developing evaluation plans for their own projects by considering stakeholders, measures, sources of evidence, and refining evaluation questions.
The New Jersey Department of Education implemented NJ SMART, a statewide longitudinal data system to store and analyze student performance data. PCG helped with a phased implementation approach to ensure proper training and adoption. The system includes a data warehouse, unique student IDs, and reporting tools. It allows the state to track student performance over time. The system improved New Jersey's score in a national education data quality survey from 0 to 8.
Learner Analytics: from Buzz to Strategic Role Academic TechnologistsJohn Whitmer, Ed.D.
This document summarizes a presentation on learner analytics. It discusses using data from learning management systems (LMS) and student information systems to better understand student learning and optimize educational environments. Specifically, it provides two case studies: 1) California State University's data dashboard that tracks graduation rates and aims to close achievement gaps. 2) CSU Chico's analysis of LMS usage data from its Vista system to examine relationships between technology use and student achievement. The presentation calls on academic technologists to lead efforts in learner analytics due to their expertise in educational technology and data. It provides resources to help campuses build capacity for analytics.
This document provides a summary of a presentation on learner analytics. It begins with an outline of the presentation which includes situating analytics, academic analytics using a case study of CSU's data dashboard, learner analytics using a case study of CSU Chico, promising efforts and resources, and a question and answer section. It then discusses academic analytics and how it uses large data sets and statistical modeling to improve decision making. A case study is presented on CSU's graduation initiative data dashboard which tracks metrics to increase graduation rates. Finally, a case study is presented on learner analytics research conducted at CSU Chico analyzing relationships between LMS tool usage and student achievement.
1. The document discusses the prospects for using learning analytics to achieve adaptive learning models. It describes adaptive learning and different levels of adaptive technologies, including platforms that react to individual user data and those that leverage aggregated data across users.
2. It outlines the pathway to achieving adaptive learning analytics, including using LMS analytics dashboards, predictive analytics, and adaptive learning analytics. Case studies and examples of existing applications are provided.
3. A proof of concept reference model for learning analytics is proposed, including a basic analytics process and an advanced process using predictive and adaptive algorithms. Linked open data for connecting curriculum standards and digital resources is also discussed.
Recent trends and issues in assessment and evaluationROOHASHAHID1
1. The document discusses recent trends and issues in educational assessment and evaluation. It covers topics such as putting students at the center, building capacity at all levels of education systems, managing local needs, greater use of technology, and shifts towards more holistic and demonstration-based forms of assessment.
2. Key trends discussed include expanding the scope of evaluation beyond just student assessment, increasing use of data and technology to enhance assessment, and growing internationalization and standardization of assessment.
3. Issues addressed involve ensuring appropriate and valid assessment methods that align with learning objectives, evaluating new skills developed through technology, and considering the policy impacts of assessment.
OECD Review on Evaluation and Assessment Frameworks for Improving School Outc...EduSkills OECD
OECD Conference Educating for Innovative Societies on 26 April 2012 - Session 5: Assessments for Skills in Thinking and Creativity - OECD Review on Evaluation and Assessment Frameworks for Improving School Outcomes by Deborah Nusche
Research study: (lif)e-portfolio by Lee Ballantyne Lee Ballantyne
This document provides a summary of a research study examining e-portfolios in the context of their implementation by Cambridge International Examinations and University of Cambridge ESOL Examinations. The study explored current drivers and issues regarding e-portfolios, as well as stakeholder requirements. It involved focus groups with CIE/ESOL representatives and interviews with teachers/candidates. The study found e-portfolios could help address increasing assessment needs while developing skills like reflection, collaboration, and self-directed learning if implemented with these benefits in mind. A framework for implementation emerged that may help inform related projects and prevent "reinventing the wheel."
The document discusses a district rollout plan for collaborative data analysis in PUSD from 2009-2010. The goal was to provide teachers with ongoing tools and processes to introduce data to staff to improve instruction. Key aspects included analyzing CST cluster data through an inquiry cycle, reviewing overall test results, and participating in classroom-level data reviews. A variety of assessment types would be used, including formative, summative, screening, and diagnostic tests. Teachers would analyze large group CST cluster reports using a provided worksheet and agenda as a guide.
Identifying the Key Factors of Training Technical School and College Teachers...ijtsrd
According to the Bangladesh Bureau of Statistics BBS , the literacy rate in Bangladesh is increasing day by day. But, Its not acceptable to our present day. The role model of an education system is a teacher or instructor. Proper education can improve our literacy rate and also be a huge change for our future Digital Bangladesh. This enhancement is only possible to highly trained instructors or teachers. In order to improve an organizations training process, it’s important to assess how instructors are trained their students. This research has worked on identifying the key factors of training Technical School and College teachers in Bangladesh. The proposed work is conducted by Data Mining and Machine Learning. The methods of this experiment are Data Processing, Data Mining, and Analysis and Evaluation. Filtering our data is completed by using the Data Processing method. After that, the datasets are trained and tested by the Data Mining and Machine Learning tools. Finally, the experimental results are evaluated and analyzed by the different assessment tools. The accuracy of our trained models are 0.97 , 0.97 , 0.96 , 0.96 , 0.96 , 0.96 , 0.94 , 0.93 , 0.93 , 0.92 , 0.91 , 0.33 , 0.22 using the Logistic Regression, Extra Trees Classifier, Random Forest Classifier, Gradient Boosting Classifier, Light Gradient Boosting Machine, SVM Linear Kernel, Ada Boost Classifier, K Neighbors Classifier, Linear Discriminant Analysis, Decision Tree Classifier, Ridge Classifier, Quadratic Discriminant Analysis, Naive Bayes, respectively. As a result, the Logistic Regression does accurately identify and classify the key factors of training Technical School and College teachers. The Logistic Regression model accuracy is 0.97 which gives better accuracy than other machine learning algorithms. Md. Mehedi Hasan | Md. Imran Ali | Nakib Aman Turzo | Golam Rabbani "Identifying the Key Factors of Training Technical School and College Teachers in Bangladesh Using Data Mining" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-1 , December 2021, URL: https://www.ijtsrd.com/papers/ijtsrd47901.pdf Paper URL: https://www.ijtsrd.com/computer-science/data-miining/47901/identifying-the-key-factors-of-training-technical-school-and-college-teachers-in-bangladesh-using-data-mining/md-mehedi-hasan
From Data To Information Perspectives On Policy And PracticeJeff_Watson
The document summarizes the Milwaukee Public Schools' (MPS) efforts to develop a comprehensive data warehouse and integrated resource information system (IRIS) to support data-informed decision making and school improvement. Key points include:
- MPS has been working with university partners for over 10 years to build its data warehouse and use data to evaluate programs and student outcomes.
- Recent focus has been on redesigning the data warehouse to improve functionality, data quality, and user support. IRIS aims to connect resource allocation and expenditure data to student outcomes.
- Early successes of IRIS include improved data quality, tracking professional development and site-based resource allocation. Further work is needed to fully integrate systems and support
Trends and Opportunities in K-12 Assessment: The New Era of ESSAEric Skuse
The Every Student Succeeds Act (ESSA) transfers decision making power around K-12 assessment and school accountability policy to states, opening up the possibilities for new measurement methods of student progress like social & emotional learning (SEL) and project-based learning (PBL).
Target Setting as a Principal Leadership Strategy to Enhance Academic Achieve...ijtsrd
Target setting is typically the result of a subjective process in which school leaders principals combine intellectual capital to establish performance expectations for their students. Target setting is widely used by school leaders to promote success, and it has been shown to improve academic achievement in students. This study looked empirically at target setting as a primary leadership strategy for improving academic achievement. The findings indicated that setting goals would likely improve the academic achievement of girls in secondary schools in Bungoma County, Kenya. Target setting supervision, level of target setting, and importance of target setting all influenced the academic achievement of girls in Bungoma County secondary schools. Among the policy recommendations were that target setting be prioritized in school programs because it has shown to have a positive relationship with academic achievement, and that all aspects of target setting, including its importance, the different levels of target setting, and its goals, be effectively communicated to all relevant stakeholders so that they all own the process and work together to achieve the desired goals. Margaret Nyilile Kataka | Simon Kipkenei | Abuya Joshua Olang’o "Target Setting as a Principal Leadership Strategy to Enhance Academic Achievement of Girls in Secondary Schools in Kenya" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-7 , December 2022, URL: https://www.ijtsrd.com/papers/ijtsrd52615.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/52615/target-setting-as-a-principal-leadership-strategy-to-enhance-academic-achievement-of-girls-in-secondary-schools-in-kenya/margaret-nyilile-kataka
The data team shared various data with the goal of understanding student success at the college. They presented data on courses with the highest enrollments and lowest retention rates broken down by demographics. Data on placement testing, financial aid, and the demographics of first-time students was also analyzed. Persistence rates for first-time students were found to be lowest for African American males, African American females, Hispanic males, and White males over five years. The data team aims to use this information to identify underlying factors impacting student success and inform interventions.
Closing the Knowledge Gap Between Evaluators and StakeholdersCesToronto
This document summarizes a presentation on closing the knowledge gap between evaluators and stakeholders. It discusses useful evaluator attitudes, aptitudes and skills, as well as evaluation methodologies that integrate opportunities for learning. Specifically, it presents the concentric circles methodology and snowball methodology, highlighting how each approach allows evaluators to gradually build knowledge and refine their evaluation. It also examines how computer-assisted qualitative data analysis software (CAQDAS) can enhance evaluator learning and evaluation quality, but notes its underutilization in the evaluation field. The presentation demonstrates the capabilities of Atlas.ti software.
Assessment in the Curriculum Design Process Peter Gow
This is a (longish) PPT deck (in PDF form here) has been my evolving script for school workshops on what assessment is, how to do it, and how to think about it. The slides by themselves are not so long a read and serve as kind of an intro–to–intermediate-level text.
Independent Curriculum Group 2015 Survey on Academic LeadershipPeter Gow
An brief report-out on results of the ICG's 2015 Academic Leadership Survey as presented at the Fall 2015 Academic Leaders Retreats. Focus is on role-specific issues for leaders and "middle managers" in schools
More Related Content
Similar to Assessing 21st-Century Learning Capacities
Confronting Reality with Big Data & Learning Analytics
We are experiencing an explosion in the quantity of data available online from archives and live streams. Learning Analytics is concerned with how educational research, and learning platform design, can make more effective use of such data (Long & Siemens, 2011). Improving outcomes through the analysis of data is of interest to researchers, administrators, systems architects, social media developers, educators and learners. Analytics are being held up by some as a way to confront, and tackle, the tough new realities of less money, less attention, and higher accountability for quality of learning.
Researchers and vendors are building reporting capabilities into tools that provide unprecedented levels of data on learners. This symposium will show what is possible, and what's coming soon. What objections could possibly be raised to such progress?
However, information infrastructure embodies and shapes worldviews: classification schemes are not only systematic ways to capture and preserve, but also to forget, by virtue of what remains invisible (Bowker & Star, 1999). Learning analytics and recommendation engines are designed with a particular conception of ‘success’, driving the patterns deemed to be evidence of progress, the interventions that are deemed appropriate, the data captured and the rules that fire in software.
This symposium will air some of the critical arguments around the limits of decontextualised data and automated analytics, which often appear reductionist in nature, failing to illuminate higher order learning. There are complex ethical issues around data fusion, and it is not clear to what extent learners are empowered, in contrast to being merely the objects of tracking technology. Educators may also find themselves at the receiving end of a new battery of institutional ‘performance indicators’ that do not reflect what they consider to be authentic learning and teaching.
This Symposium will provide the opportunity to hear a series of brief presentations introducing contrasting perspectives, before the debate is opened to all. Speakers from a cross-section of The Open University will describe how we are connecting datasets, analysing student data and prototyping next generation analytics. Complementing this, JISC will present a national capability perspective, with an update on the JISC CETIS ‘landscape analysis’ of the field, which will clarify potential benefits, issues to consider, and help institutions to assess their current capability and possible next steps.
Participants will catch up with developments in this fast moving field, through exposure to the possibilities of analytics, as well as issues to be alert to.
1) The document discusses social learning analytics, which examines how learners interact and engage in social learning networks, discourses, and contexts.
2) It presents a taxonomy of social learning analytics, including social network analysis, discourse analysis, content analysis, analysis of learning dispositions, and analysis of social learning contexts.
3) The discussion emphasizes that social learning analytics should not just track what learners do, but also how the data is used to provide formative feedback and help learners grow, moving beyond just institutional tracking of students.
This document summarizes the Assessment of Higher Education Learning Outcomes (AHELO) feasibility study being conducted by the OECD. The study aims to assess learning outcomes in higher education on an international scale using measures that are valid across cultures and institutions. It will test the feasibility of reliably measuring generic skills as well as discipline-specific competencies in economics and engineering. The study involves developing assessment instruments, implementing them in a small pilot test involving multiple countries, and collecting contextual data about institutions and students. The goal is to provide a proof of concept for assessing higher education quality through learning outcomes while respecting institutional diversity.
Designing useful evaluations - An online workshop for the Jisc AF programme_I...Rachel Harris
This document summarizes a workshop on designing useful evaluations for projects funded by the JISC and Becta Curriculum Delivery Programme. The workshop covered the evaluation cycle, identifying intended outcomes and impact, determining what to evaluate, developing evaluation questions, and methods for undertaking evaluations. Examples of evaluation approaches used by different projects were discussed, including action research, external evaluators, and using both qualitative and quantitative data sources. Participants were guided in developing evaluation plans for their own projects by considering stakeholders, measures, sources of evidence, and refining evaluation questions.
The New Jersey Department of Education implemented NJ SMART, a statewide longitudinal data system to store and analyze student performance data. PCG helped with a phased implementation approach to ensure proper training and adoption. The system includes a data warehouse, unique student IDs, and reporting tools. It allows the state to track student performance over time. The system improved New Jersey's score in a national education data quality survey from 0 to 8.
Learner Analytics: from Buzz to Strategic Role Academic TechnologistsJohn Whitmer, Ed.D.
This document summarizes a presentation on learner analytics. It discusses using data from learning management systems (LMS) and student information systems to better understand student learning and optimize educational environments. Specifically, it provides two case studies: 1) California State University's data dashboard that tracks graduation rates and aims to close achievement gaps. 2) CSU Chico's analysis of LMS usage data from its Vista system to examine relationships between technology use and student achievement. The presentation calls on academic technologists to lead efforts in learner analytics due to their expertise in educational technology and data. It provides resources to help campuses build capacity for analytics.
This document provides a summary of a presentation on learner analytics. It begins with an outline of the presentation which includes situating analytics, academic analytics using a case study of CSU's data dashboard, learner analytics using a case study of CSU Chico, promising efforts and resources, and a question and answer section. It then discusses academic analytics and how it uses large data sets and statistical modeling to improve decision making. A case study is presented on CSU's graduation initiative data dashboard which tracks metrics to increase graduation rates. Finally, a case study is presented on learner analytics research conducted at CSU Chico analyzing relationships between LMS tool usage and student achievement.
1. The document discusses the prospects for using learning analytics to achieve adaptive learning models. It describes adaptive learning and different levels of adaptive technologies, including platforms that react to individual user data and those that leverage aggregated data across users.
2. It outlines the pathway to achieving adaptive learning analytics, including using LMS analytics dashboards, predictive analytics, and adaptive learning analytics. Case studies and examples of existing applications are provided.
3. A proof of concept reference model for learning analytics is proposed, including a basic analytics process and an advanced process using predictive and adaptive algorithms. Linked open data for connecting curriculum standards and digital resources is also discussed.
Recent trends and issues in assessment and evaluationROOHASHAHID1
1. The document discusses recent trends and issues in educational assessment and evaluation. It covers topics such as putting students at the center, building capacity at all levels of education systems, managing local needs, greater use of technology, and shifts towards more holistic and demonstration-based forms of assessment.
2. Key trends discussed include expanding the scope of evaluation beyond just student assessment, increasing use of data and technology to enhance assessment, and growing internationalization and standardization of assessment.
3. Issues addressed involve ensuring appropriate and valid assessment methods that align with learning objectives, evaluating new skills developed through technology, and considering the policy impacts of assessment.
OECD Review on Evaluation and Assessment Frameworks for Improving School Outc...EduSkills OECD
OECD Conference Educating for Innovative Societies on 26 April 2012 - Session 5: Assessments for Skills in Thinking and Creativity - OECD Review on Evaluation and Assessment Frameworks for Improving School Outcomes by Deborah Nusche
Research study: (lif)e-portfolio by Lee Ballantyne Lee Ballantyne
This document provides a summary of a research study examining e-portfolios in the context of their implementation by Cambridge International Examinations and University of Cambridge ESOL Examinations. The study explored current drivers and issues regarding e-portfolios, as well as stakeholder requirements. It involved focus groups with CIE/ESOL representatives and interviews with teachers/candidates. The study found e-portfolios could help address increasing assessment needs while developing skills like reflection, collaboration, and self-directed learning if implemented with these benefits in mind. A framework for implementation emerged that may help inform related projects and prevent "reinventing the wheel."
The document discusses a district rollout plan for collaborative data analysis in PUSD from 2009-2010. The goal was to provide teachers with ongoing tools and processes to introduce data to staff to improve instruction. Key aspects included analyzing CST cluster data through an inquiry cycle, reviewing overall test results, and participating in classroom-level data reviews. A variety of assessment types would be used, including formative, summative, screening, and diagnostic tests. Teachers would analyze large group CST cluster reports using a provided worksheet and agenda as a guide.
Identifying the Key Factors of Training Technical School and College Teachers...ijtsrd
According to the Bangladesh Bureau of Statistics BBS , the literacy rate in Bangladesh is increasing day by day. But, Its not acceptable to our present day. The role model of an education system is a teacher or instructor. Proper education can improve our literacy rate and also be a huge change for our future Digital Bangladesh. This enhancement is only possible to highly trained instructors or teachers. In order to improve an organizations training process, it’s important to assess how instructors are trained their students. This research has worked on identifying the key factors of training Technical School and College teachers in Bangladesh. The proposed work is conducted by Data Mining and Machine Learning. The methods of this experiment are Data Processing, Data Mining, and Analysis and Evaluation. Filtering our data is completed by using the Data Processing method. After that, the datasets are trained and tested by the Data Mining and Machine Learning tools. Finally, the experimental results are evaluated and analyzed by the different assessment tools. The accuracy of our trained models are 0.97 , 0.97 , 0.96 , 0.96 , 0.96 , 0.96 , 0.94 , 0.93 , 0.93 , 0.92 , 0.91 , 0.33 , 0.22 using the Logistic Regression, Extra Trees Classifier, Random Forest Classifier, Gradient Boosting Classifier, Light Gradient Boosting Machine, SVM Linear Kernel, Ada Boost Classifier, K Neighbors Classifier, Linear Discriminant Analysis, Decision Tree Classifier, Ridge Classifier, Quadratic Discriminant Analysis, Naive Bayes, respectively. As a result, the Logistic Regression does accurately identify and classify the key factors of training Technical School and College teachers. The Logistic Regression model accuracy is 0.97 which gives better accuracy than other machine learning algorithms. Md. Mehedi Hasan | Md. Imran Ali | Nakib Aman Turzo | Golam Rabbani "Identifying the Key Factors of Training Technical School and College Teachers in Bangladesh Using Data Mining" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-1 , December 2021, URL: https://www.ijtsrd.com/papers/ijtsrd47901.pdf Paper URL: https://www.ijtsrd.com/computer-science/data-miining/47901/identifying-the-key-factors-of-training-technical-school-and-college-teachers-in-bangladesh-using-data-mining/md-mehedi-hasan
From Data To Information Perspectives On Policy And PracticeJeff_Watson
The document summarizes the Milwaukee Public Schools' (MPS) efforts to develop a comprehensive data warehouse and integrated resource information system (IRIS) to support data-informed decision making and school improvement. Key points include:
- MPS has been working with university partners for over 10 years to build its data warehouse and use data to evaluate programs and student outcomes.
- Recent focus has been on redesigning the data warehouse to improve functionality, data quality, and user support. IRIS aims to connect resource allocation and expenditure data to student outcomes.
- Early successes of IRIS include improved data quality, tracking professional development and site-based resource allocation. Further work is needed to fully integrate systems and support
Trends and Opportunities in K-12 Assessment: The New Era of ESSAEric Skuse
The Every Student Succeeds Act (ESSA) transfers decision making power around K-12 assessment and school accountability policy to states, opening up the possibilities for new measurement methods of student progress like social & emotional learning (SEL) and project-based learning (PBL).
Target Setting as a Principal Leadership Strategy to Enhance Academic Achieve...ijtsrd
Target setting is typically the result of a subjective process in which school leaders principals combine intellectual capital to establish performance expectations for their students. Target setting is widely used by school leaders to promote success, and it has been shown to improve academic achievement in students. This study looked empirically at target setting as a primary leadership strategy for improving academic achievement. The findings indicated that setting goals would likely improve the academic achievement of girls in secondary schools in Bungoma County, Kenya. Target setting supervision, level of target setting, and importance of target setting all influenced the academic achievement of girls in Bungoma County secondary schools. Among the policy recommendations were that target setting be prioritized in school programs because it has shown to have a positive relationship with academic achievement, and that all aspects of target setting, including its importance, the different levels of target setting, and its goals, be effectively communicated to all relevant stakeholders so that they all own the process and work together to achieve the desired goals. Margaret Nyilile Kataka | Simon Kipkenei | Abuya Joshua Olang’o "Target Setting as a Principal Leadership Strategy to Enhance Academic Achievement of Girls in Secondary Schools in Kenya" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-7 , December 2022, URL: https://www.ijtsrd.com/papers/ijtsrd52615.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/52615/target-setting-as-a-principal-leadership-strategy-to-enhance-academic-achievement-of-girls-in-secondary-schools-in-kenya/margaret-nyilile-kataka
The data team shared various data with the goal of understanding student success at the college. They presented data on courses with the highest enrollments and lowest retention rates broken down by demographics. Data on placement testing, financial aid, and the demographics of first-time students was also analyzed. Persistence rates for first-time students were found to be lowest for African American males, African American females, Hispanic males, and White males over five years. The data team aims to use this information to identify underlying factors impacting student success and inform interventions.
Closing the Knowledge Gap Between Evaluators and StakeholdersCesToronto
This document summarizes a presentation on closing the knowledge gap between evaluators and stakeholders. It discusses useful evaluator attitudes, aptitudes and skills, as well as evaluation methodologies that integrate opportunities for learning. Specifically, it presents the concentric circles methodology and snowball methodology, highlighting how each approach allows evaluators to gradually build knowledge and refine their evaluation. It also examines how computer-assisted qualitative data analysis software (CAQDAS) can enhance evaluator learning and evaluation quality, but notes its underutilization in the evaluation field. The presentation demonstrates the capabilities of Atlas.ti software.
Assessment in the Curriculum Design Process Peter Gow
This is a (longish) PPT deck (in PDF form here) has been my evolving script for school workshops on what assessment is, how to do it, and how to think about it. The slides by themselves are not so long a read and serve as kind of an intro–to–intermediate-level text.
Independent Curriculum Group 2015 Survey on Academic LeadershipPeter Gow
An brief report-out on results of the ICG's 2015 Academic Leadership Survey as presented at the Fall 2015 Academic Leaders Retreats. Focus is on role-specific issues for leaders and "middle managers" in schools
Workshop session on "How Schools Build Innovative Curriculum" from the Independent Curriculum Group conference, "Re-Imagining High School," October 27, 2009 at Beaver Country Day School in Chestnut Hill, Massachusetts.
Presentation on one view of the evolution of progressive education in the 21st century, originally made for the Progressive Education Network national conference in October 2009.
A rubric is a tool used to assess student performance on assignments and provide feedback. It defines the expectations and objectives of the assignment and describes what constitutes high quality performance. Developing rubrics with students helps them understand what is expected of their work. Using rubrics provides specific feedback and makes grading more consistent and objective. It also helps students understand how to improve by focusing on the objectives. There are different types of rubrics such as numeric scales and qualitative descriptions. Regardless of the type, rubrics should clearly define the performance levels so students understand how their work will be evaluated.
This document discusses evaluation rubrics and provides guidance on how to create them. It defines a rubric as a set of criteria used to evaluate student work. It emphasizes that rubrics should clearly define performance levels and provide students with clear feedback. The document then provides examples of different rubric formats and discusses how to design rubrics, including identifying important evaluation categories and defining different performance levels for each category. It also provides tips on using rubrics to grade student work.
Progressive education began in the early 20th century as a reform movement aimed at moral and social transformation through child-centered educational approaches. It grew from the philosophies of thinkers like John Locke and Jean-Jacques Rousseau. Major early proponents included John Dewey and Maria Montessori. In the 1930s, the Eight-Year Study found that progressive education was as effective at preparing students for college as traditional methods. While progressive education waned in popularity in the 1950s, many of its values and approaches saw a resurgence in the 1960s and continue to influence education today.
The document discusses principles of effective assessment and evaluation. It states that assessment should primarily aim to improve student learning and teaching. Assessment takes a broad range of forms and should be tailored to the skills or knowledge being assessed. Effective assessment intentionally focuses on important learning goals, provides clear feedback, and is varied, manageable, timely and fair. Performance standards, rubrics, grades and evaluating effort are also discussed.
This document discusses theories of learning and intelligence. It covers the following key points:
1. Individuals have different learning styles based on their innate cognitive systems and life experiences. No two people learn the same way.
2. The brain needs certain inputs like water, oxygen, and stimulation to function well. It also benefits from repetition, strong associations, patterns, and positive reinforcement.
3. Modern theories of intelligence reject the idea of a single measurable intelligence, and instead see intelligence as comprising multiple capacities or dispositions that are contextual.
The document provides guidance on effective curriculum design. It defines key terms like generative topic, essential question, and assessment. It recommends designing curriculum backwards, starting with identifying the overall point and desired understandings, then determining acceptable evidence and assessments, and finally planning learning experiences and instructional tasks. It discusses assessing student learning and understanding rather than making evaluations. It also presents examples of essential questions and provides models for curriculum planning and unit design.
Technology and the Culture of Learning, 2004Peter Gow
A PPT condensing an article on "Technology and the Culture of Learning" that discusses the dimensions and ramifications of technological change for schools, teaching, and learning.
Lesson Learned from a Curriculum Change ProcessPeter Gow
This document discusses lessons learned from curriculum reform efforts at schools. It emphasizes that curriculum reform is an ongoing process that requires long-term commitment and structures to ensure continuous development. It also stresses the importance of connecting reform efforts to the school's mission and strategic plan. Finally, it notes that curriculum reform is challenging and impacts all areas of the school, requiring support structures for professional development and accountability.
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
Physiology and chemistry of skin and pigmentation, hairs, scalp, lips and nail, Cleansing cream, Lotions, Face powders, Face packs, Lipsticks, Bath products, soaps and baby product,
Preparation and standardization of the following : Tonic, Bleaches, Dentifrices and Mouth washes & Tooth Pastes, Cosmetics for Nails.
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.
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
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
The simplified electron and muon model, Oscillating Spacetime: The Foundation...RitikBhardwaj56
Discover the Simplified Electron and Muon Model: A New Wave-Based Approach to Understanding Particles delves into a groundbreaking theory that presents electrons and muons as rotating soliton waves within oscillating spacetime. Geared towards students, researchers, and science buffs, this book breaks down complex ideas into simple explanations. It covers topics such as electron waves, temporal dynamics, and the implications of this model on particle physics. With clear illustrations and easy-to-follow explanations, readers will gain a new outlook on the universe's fundamental nature.
How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
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.
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
हिंदी वर्णमाला पीपीटी, hindi alphabet PPT presentation, hindi varnamala PPT, Hindi Varnamala pdf, हिंदी स्वर, हिंदी व्यंजन, sikhiye hindi varnmala, dr. mulla adam ali, hindi language and literature, hindi alphabet with drawing, hindi alphabet pdf, hindi varnamala for childrens, hindi language, hindi varnamala practice for kids, https://www.drmullaadamali.com
1. Heads Up!
The Other Kind of Assessment,
and Why It Matters
Peter Gow
(with enormous thanks to Doug Lyons, CAIS-
CT, and Andrew Niblock, Hamden Hall CDS)
ICG: New Directions in Assessment
April 21, 2012
2. 2
Your Factoid of the Day
Beginning with the current cycle,
independent school accreditation in every
region will require evidence of data-
informed decision making in the area of
academic program
Several regions (ISASW, Canada) require
school-wide (or regular and broad-based)
data-gathering on academic performance as
a part of their accreditation process
ICG April 2012 Other Assessments--Gow
3. 3
The Holy Grail
In an ideal world we would have easy access
to
assessments that measure things that our
schools claim to value
assessments that have credibility within our
wider communities as well as within our walls
assessments that generate data that is easy
both to comprehend and to translate into
better instruction and programming
assessments that are easy to administer
ICG April 2012 Other Assessments--Gow
4. 4
Some Pre-Suppositions
The new accreditation requirements are
based on some not-necessarily correct
assumptions:
2.That schools are familiar with appropriate
assessment tools that will provide useful
data
3.That schools have the expertise to make the
most skillful and informed use of data
4.That tools of the sort we need already exist
ICG April 2012 Other Assessments--Gow
6. 6
New kinds of assessments focused on
“21st-century learning capacities”
Performance-task-based:
CWRA: College and Work Readiness
Assessment (ICG folks know all about this)
C-PAS: College-readiness Performance
Assessment System (from the Educational
Policy Improvement Center—David Conley)
CBAL: Cognitively Based Assessment of, for,
and as Learning (from Educational Testing
Service)
iSkills: Information and Communication
Technology skills assessment (from ETS)
ICG April 2012 Other Assessments--Gow
7. 7
New kinds of assessments focused on
“21st-century learning capacities”
Attitudinal/motivational/”habits of
mind”-based:
HSSSE: The High School Survey of
Student Engagement (moribund for
the moment, alas)
CSEQ: College Student Experiences
Questionnaire
ISHC: Independent School Health
Check
ICG April 2012 Other Assessments--Gow
8. 8
New Ways of Engaging with
“International” Assessments
The CAIS TIMSS (Trends in International
Mathematics and Science Study) question
database—create and score your own “TIMMS”
assessment
The school-based PISA (Programme for
International Student Assessment, from the
Organisation for Economic Cooperation and
Development)
Search “released items” for real test questions
for a host of large-scale assessments (NAEP ,
state)
ICG April 2012 Other Assessments--Gow
9. 9
Squeezing More Data from Commonly
Available Assessments
Use the EXPLORE-PLAN-ACT sequence
USE that ERB data
Get the fine points from PSAT SOAS (Summary of
Answers and Skills) reports
Consider the “School-Day SAT With Enhanced
Scoring”—student and item-level data, skill reports
ICG April 2012 Other Assessments--Gow
10. For a whole lot more
information, see Lyons &
Niblock, “Measuring What We
Value” (NAISAC12):
http://www.caisct.org/RelId/630134/IS
vars/default/NAIS_PRESENTATION.htm
Editor's Notes
This is gonna be like speed-dating—quick overview only Also: marketing your school is better when the data you present isn’t just “elevating only modestly valuable information”—like college lists or the number of kids who take AP examinations
Obviously, the first one matters most—that’s what our project has been about this year
This is just here to scare you—the Commission on Accreditation has a pretty extensive report and set of recommendations based on work commissioned by NAIS at large on this
But there’s help—if you’re taking notes, just the acronyms and initials will take you where you want to go
What really matters to most of us, we could argue, is how deeply and meaningfully are our students engaged with the things that we are asking them to do? How distracted are they by things that don’t matter so much to us but that are enormously significant to them?
Truth in testing laws—New York and elsewhere. You can ask your students the same questions we find on the big international assessments whose results terrify politicians, sell newspapers by “proving” that “we suck”. Maybe you want to find out for yourself whether your school actually does, by these measures.
(These aren’t real “21st-century skill” assessments, but they can give you insight into other and important kinds of student capacities—this stuff still matters, and it doesn’t seem to be going away—but get smart about how you use it rather than letting it frighten you
It’s worth copying down the whole URL here—and we’re hoping to get Doug and Andrew to do their version at a later ICG gathering