For several decades now, assessment has become an increasingly pressing educational priority. Teacher and school accountability systems have come to be based on analysis of large-scale, standardized summative assessments. As a consequence, assessment now dominates most conversations about reform, particularly as a measure of teacher and school accountability for learner performance. Behind the often heated and at times ideologically gridlocked debate is a genuine challenge to address gaps in achievement between different demographically identifiable groups of students. There is an urgent need to lift whole communities and cohorts of students out of cycles of underachievement. For better or for worse, testing and public reporting of achievement is seen to be one of the few tools capable of clearly informing public policy makers and communities alike about how their resources are being used to expand the life opportunities for their children. This course is an overview of current debates about testing, and analyses the strengths and weaknesses of a variety of approaches to assessment. The course also focuses on the use of assessment technologies in learning. It will explore recent advances in computer adaptive and diagnostic testing, the use of natural language processing technologies in assessments, and embedded formative assessments in digital and online curricula. Other topics include the use of data mining, learning analytics and artificial intelligence in learning management systems and educational technology platforms. Participants will be required to consider issues of data access, privacy and the challenges raised by ‘big data’ including data persistency and student profiling.
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For several decades now, assessment has become an increasingly pressing educational priority. Teacher and school accountability systems have come to be based on analysis of large-scale, standardized summative assessments. As a consequence, assessment now dominates most conversations about reform, particularly as a measure of teacher and school accountability for learner performance. Behind the often heated and at times ideologically gridlocked debate is a genuine challenge to address gaps in achievement between different demographically identifiable groups of students. There is an urgent need to lift whole communities and cohorts of students out of cycles of underachievement. For better or for worse, testing and public reporting of achievement is seen to be one of the few tools capable of clearly informing public policy makers and communities alike about how their resources are being used to expand the life opportunities for their children. This course is an overview of current debates about testing, and analyses the strengths and weaknesses of a variety of approaches to assessment. The course also focuses on the use of assessment technologies in learning. It will explore recent advances in computer adaptive and diagnostic testing, the use of natural language processing technologies in assessments, and embedded formative assessments in digital and online curricula. Other topics include the use of data mining, learning analytics and artificial intelligence in learning management systems and educational technology platforms. Participants will be required to consider issues of data access, privacy and the challenges raised by ‘big data’ including data persistency and student profiling.
For several decades now, assessment has become an increasingly pressing educational priority. Teacher and school accountability systems have come to be based on analysis of large-scale, standardized summative assessments. As a consequence, assessment now dominates most conversations about reform, particularly as a measure of teacher and school accountability for learner performance. Behind the often heated and at times ideologically gridlocked debate is a genuine challenge to address gaps in achievement between different demographically identifiable groups of students. There is an urgent need to lift whole communities and cohorts of students out of cycles of underachievement. For better or for worse, testing and public reporting of achievement is seen to be one of the few tools capable of clearly informing public policy makers and communities alike about how their resources are being used to expand the life opportunities for their children. This course is an overview of current debates about testing, and analyses the strengths and weaknesses of a variety of approaches to assessment. The course also focuses on the use of assessment technologies in learning. It will explore recent advances in computer adaptive and diagnostic testing, the use of natural language processing technologies in assessments, and embedded formative assessments in digital and online curricula. Other topics include the use of data mining, learning analytics and artificial intelligence in learning management systems and educational technology platforms. Participants will be required to consider issues of data access, privacy and the challenges raised by ‘big data’ including data persistency and student profiling.
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Recommended Background
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This course is designed for people interested in the future of education and the "learning society," including people who may wish to join education as a profession, practicing teachers interested in exploring future directions for a vocation that is currently undergoing transformation, and community and workplace leaders who regard their mission to be in part "educative."
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Related Resources
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Online resources are available here:
https://newlearningonline.com
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Join our Online Communities!
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CGScholar (Create an account and join the New Learning community)
https://cgscholar.com/community/community_profiles/new-learning/community_updates
https://www.facebook.com/newlearningonline
https://twitter.com/neolearning
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Take this Course for Credit at the University of Illinois
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This course has the same content and anticipates the same level of contribution by students in the Assessment for Learning course offered to graduate certificate, masters, and doctoral level students in the Learning Design and Leadership Program in the College of Education at the University of Illinois.
Of course, in the nature of MOOCs many people will just want to view the videos and casually join some of the discussions. Some people say that these limited kinds of participation offer evidence that MOOCs suffer from low retention rates. Far from it – we say that any level of engagement is good engagement.
On the other hand, if you would like to take this course for credit at the University of Illinois, you will find more information about our program here:
https://ldlprogram.web.illinois.edu/overview/
And you can apply here:
https://education.illinois.edu/epol/programs-degrees/ldl
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The Learning Design and Leadership Series of MOOCs
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This course is one of a series of eight MOOCs created by Bill Cope and Mary Kalantzis for the Learning Design and Leadership program at the University of Illinois. If you find this MOOC helpful, please join us in others!
e-Learning Ecologies: Innovative Approaches to Teaching and Learning for the Digital Age
https://www.coursera.org/learn/elearning
New Learning: Principles and Patterns of Pedagogy
https://www.coursera.org/learn/newlearning
Assessment for Learning
https://www.coursera.org/learn/assessmentforlearning
Learning, Knowledge, and Human Development
https://www.coursera.org/learn/learning-knowledge-human-development
Ubiquitous Learning and Instructional Technologies
https://www.coursera.org/learn/ubiquitouslearning
Negotiating Learner Differences: Towards Productive Diversity in Learning
https://www.coursera.org/learn/learnerdifferences
Literacy Teaching and Learning: Aims, Approaches and Pedagogies
https://www.coursera.org/learn/literacy-teaching-learning
Multimodal Literacies: Communication and Learning in the Era of Digital Media
https://www.coursera.org/learn/multimodal-literacies
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Syllabus
Course Orientation + Intelligence Tests
This course is an overview of current debates about testing, and analyses of the strengths and weaknesses of a variety of approaches to assessment. The module also focuses on the use of assessment technologies in learning. It will explore recent advances in computer adaptive and diagnostic testing, the use of natural language processing technologies in assessments, and embedded formative assessments in digital and online curricula. Other topics include the use of data mining and learning analytics in learning management systems and educational technology platforms. The module also considers issues of data access, privacy, and the challenges raised by ‘big data’ including data persistency and student profiling. A final section addresses the processes of educational evaluation. Video presenters include Mary Kalantzis, Bill Cope, Luc Paquette, and Jennifer Greene.
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Reviews summary
Assessment for educators
Makes assessment accessible
Provides an opportunity to give and receive feedback
Easy to understand for those new to assessment
Reviews key concepts in assessment
Experienced and knowledgeable
Covers a variety of important topics
Valuable information for educators
Activities
Form a study group to discuss assessment topics
Show steps
Join or form a study group to engage in discussions, share insights, and support each other's learning in the course.
Show steps
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Identify or form a study group with peers.
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Schedule regular study sessions.
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Discuss course materials, concepts, and assessment strategies.
-
Support and motivate each other.
Review advanced assessment techniques
Show steps
Refresh your knowledge of advanced assessment techniques to enhance your understanding of the course content.
Browse courses on
Assessment for Learning
Show steps
-
Revisit readings or notes on advanced assessment techniques.
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Practice creating different types of assessments, such as computer adaptive tests or formative assessments.
-
Reflect on the strengths and weaknesses of various assessment techniques.
Volunteer as an assessment reviewer
Show steps
Volunteer to review assessments for organizations or institutions, gaining hands-on experience in evaluating student work and contributing to assessment practices.
Browse courses on
Peer Assessment
Show steps
-
Identify opportunities to volunteer as an assessment reviewer.
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Review assessment materials and provide feedback.
-
Participate in discussions and collaborate with other reviewers.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Explore learning analytics platforms
Show steps
Gain hands-on experience with learning analytics platforms to develop a practical understanding of their capabilities.
Browse courses on
Learning Analytics
Show steps
-
Identify a learning analytics platform of interest.
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Follow tutorials or documentation to learn how to use the platform.
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Experiment with different features and functionalities.
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Analyze sample data to gain insights into student learning.
Develop an assessment plan
Show steps
Create a comprehensive assessment plan that aligns with the learning objectives of the course, demonstrating your understanding of assessment principles.
Show steps
-
Determine the learning objectives for the assessment.
-
Select appropriate assessment methods and techniques.
-
Develop assessment rubrics or scoring criteria.
-
Consider ethical and bias considerations in assessment.
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Plan for assessment implementation and evaluation.
Analyze assessment data
Show steps
Practice analyzing assessment data to identify trends, patterns, and areas for improvement in teaching and learning.
Browse courses on
Data Analysis
Show steps
-
Collect and organize assessment data.
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Use statistical and visualization techniques to analyze data.
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Interpret results and draw conclusions.
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Develop recommendations for improving assessment practices.
Contribute to open-source assessment projects
Show steps
Get involved in open-source projects to gain practical experience in assessment technology and contribute to the field.
Show steps
-
Identify open-source assessment projects.
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Review project documentation and code.
-
Contribute code, documentation, or other resources.
-
Collaborate with other contributors.
Form a study group to discuss assessment topics
Show steps
Join or form a study group to engage in discussions, share insights, and support each other's learning in the course.
Show steps
- Identify or form a study group with peers.
- Schedule regular study sessions.
- Discuss course materials, concepts, and assessment strategies.
- Support and motivate each other.
Review advanced assessment techniques
Show steps
Refresh your knowledge of advanced assessment techniques to enhance your understanding of the course content.
Browse courses on
Assessment for Learning
Show steps
- Revisit readings or notes on advanced assessment techniques.
- Practice creating different types of assessments, such as computer adaptive tests or formative assessments.
- Reflect on the strengths and weaknesses of various assessment techniques.
Volunteer as an assessment reviewer
Show steps
Volunteer to review assessments for organizations or institutions, gaining hands-on experience in evaluating student work and contributing to assessment practices.
Browse courses on
Peer Assessment
Show steps
- Identify opportunities to volunteer as an assessment reviewer.
- Review assessment materials and provide feedback.
- Participate in discussions and collaborate with other reviewers.
Explore learning analytics platforms
Show steps
Gain hands-on experience with learning analytics platforms to develop a practical understanding of their capabilities.
Browse courses on
Learning Analytics
Show steps
- Identify a learning analytics platform of interest.
- Follow tutorials or documentation to learn how to use the platform.
- Experiment with different features and functionalities.
- Analyze sample data to gain insights into student learning.
Develop an assessment plan
Show steps
Create a comprehensive assessment plan that aligns with the learning objectives of the course, demonstrating your understanding of assessment principles.
Show steps
- Determine the learning objectives for the assessment.
- Select appropriate assessment methods and techniques.
- Develop assessment rubrics or scoring criteria.
- Consider ethical and bias considerations in assessment.
- Plan for assessment implementation and evaluation.
Analyze assessment data
Show steps
Practice analyzing assessment data to identify trends, patterns, and areas for improvement in teaching and learning.
Browse courses on
Data Analysis
Show steps
- Collect and organize assessment data.
- Use statistical and visualization techniques to analyze data.
- Interpret results and draw conclusions.
- Develop recommendations for improving assessment practices.
Contribute to open-source assessment projects
Show steps
Get involved in open-source projects to gain practical experience in assessment technology and contribute to the field.
Show steps
- Identify open-source assessment projects.
- Review project documentation and code.
- Contribute code, documentation, or other resources.
- Collaborate with other contributors.
Career center
Assessment Specialist
Measurement and Evaluation Specialist
Learning Scientist
Educational Data Analyst
Education Policy Analyst
Curriculum Developer
Instructional Designer
Education Consultant
Educational Technologist
Teacher
School Administrator
Corporate Trainer
Higher Education Administrator
Educational Researcher
Nonprofit Program Manager
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