Pplus_short_TA3_DIGI

Index

Introduction of Module

Supporting materials

Resources, Glossary

Preliminary Assessment

Learning materials

Mind Map

Unit 3 .1

Utilisation of digital technologies for diverse and appropriate assessments

Case Study

Unit 3.2

Analysis and interpretation of learning evidences, assessment data and measurement results

Sum up Infographic

Unit 3.3

Effective feedback and support students to develop their learning practice

Final Quiz - Survey - Badge

Testimonial

Assessment determines the entire educational process and is an integral part of the teaching-learning. Digital technologies and tools enrich modes and ways of assessment and can effectively support and improve learning. Let’s see what solutions are provided by digital assessment.

Welcome to our innovative course Digitalization in Learning and Teaching

Intoduction Course

• In this comprehensive course we aim to equip teachers with the necessary skills and strategies to effectively embed digitalization techniques into their teaching practices, fostering a more digitally inclined approach among students.
• Throughout the course, you will explore a wide range of topics, including leveraging educational technology tools, designing engaging digital learning experiences, promoting digital literacy and developing digital skills, and nurturing critical thinking in a digital context.
• We will delve into practical methodologies for incorporating interactive multimedia content, online collaboration platforms, and personalized learning approaches.
• By the end of this course, you will have gained the knowledge and confidence to create dynamic digital learning environments that inspire and empower students to thrive in today's increasingly digital world.

Intoduction Module

In this module you will learn how to use digital technologies for the development of assessment, to analyse students’ performance and to give effective feedback so as to support learning.

Learning outcomes of the module:

To develop assessment utilizing appropriate digital technologies and tools.

To adequately interpret learning evidence and data.

To provide effective feedback to students with the support of digital tools.

To develop follow-up steps to improve learning and teaching.

This module addresses teachers working within any field of study and proposes general tips on how to improve assessment by using digital solutions to enhance and improve teaching and learning. The module also provides practical exercises, a wide range of resources, and checklists for self-assessments.

Keywords: assessment, digital assessment, digital technologies for assessment, learning evidence and data, learning analytics, effective feedback, self-regulated learning (SRL)

Self-regulated learning

Personalisation of learning

AI for assessment

Learning analytics

Learning evidence and data

Digital tools for assessment

Digital technologies and tools for assessment

Digital assessment

Effective feedback

Diagnostic assessment

Summative assessment

Formative assessment

Mindmap of the topic

Self-reflection

Assessment Tool

Statements

Assess your competence in Student’s learning assessment by the PROFFORMANCE Assessment Tool.

Assess yourself along the PROFFORMANCE Assessment tool statements DIGI TA3 - Competences on innovative teaching and learning

What is your experience?

Self-reflection is a valuable tool when developing your course. It helps you identify your strengths and areas for improvement. Our course supports you in strengthening your weaknesses and designing a better learning experience for your students.

This is a paragraph of text waiting to be awesome content

I utilize digital technologies for diverse and appropriate formative and summative assessments.

Assess yourself

Hint

I create, critically analyse, and interpret digital data on student’s activities, performance and progress.

Assess yourself

Hint

I use digital technology to provide timely, targeted and clear feedback to students.

Assess yourself

Hint

I adapt learning practices and provide support according to the results generated using digital technologies.

Assess yourself

Hint

This is a paragraph of text waiting to be awesome content

UNIT 3.1

Utilisation of digital technologies for diverse and appropriate assessments

In this unit we will focus :

• What means digital assessment.
• Which kind of strategies we can use for digital assessment.
• Which factors we should be aware regarding digital assessment.

'Learners need endless feedback more than they need endless teaching.' - Grant Wiggins

UNIT 3.1

Utilisation of digital technologies for diverse and appropriate assessments

Basic features of digital assessment:

Advantages of Digital Assessment:

Technology-enabled assessment

Efficiency and Speed

Data Analytics

Automated feedback and scoring

Flexibility and Accessibility

Personalized Learning

Accessibility and flexibility

Versatility

Engagement

Data-driven insights

Environmentally Friendly

UNIT 3.1

Assessment strategies

When designing assessment, starting with elaboration of an assessment strategy

Assessment strategy

sets clear goals and expectations of assessment and provides students with opportunities to self-assess, peer-assess, and receive feedback,

is aligned with learning outcomes

sets a variety of assessment methods

identifies multiple modes of representation and demonstration of what students learned

identifies a wide range of tools to monitor learner progress and evaluate achievements

defines forms and types of feedback to provide differentiated and personlalised support

Watch

UNIT 3.1

Selecting digital tools for different forms of assessment

Formative Assessment Tools

Selecting the right assessment tool depends on several factors:

• Type and purpose of assessment

Summative Assessment Tools

• Learning objectives

• Discipline-specific needs

Diagnostic Assessment Tools

• Class size

• Feedback mechanisms

Performance-Based Assessment Tools

• Technology integration

Learning Analytics and Data Tools

Incorporating a mix of these tools can create a robust and well-rounded assessment strategy that supports diverse and differentiated learning.

UNIT 3.1

University’s assessment framework

Below there are 3 universities’s assessment frameworks providing detailed guidance and practices for evaluating student learning.

Vanderbilt University

Dartmouth College

Columbia University

UNIT 3.1

10.

Reflection exercise

1.

2.

9.

3.

8.

4.

6.

5.

7.

UNIT 3.1

Conclusions

Summary of the unit content

Digital Assessment Defined: Digital assessment leverages technology to evaluate student performance through various methods like online quizzes, assignments, and portfolios. It offers features like automated feedback, accessibility, and data-driven insights.

Designing an Effective Assessment Strategy: A well-designed assessment strategy is crucial. It should include clear goals, alignment with learning outcomes, a variety of assessment methods, diverse modes of representation, a range of tools, and personalized feedback.

Selecting and Utilizing Digital Assessment Tools: Choosing the right digital tools is essential. Consider the assessment type and purpose, learning objectives, discipline-specific needs, class size, feedback mechanisms, and technology integration. A mix of tools, including formative, summative, diagnostic, and performance-based assessment tools, can provide a robust assessment strategy.

Benefits of Digital Assessment: Digital assessment offers numerous advantages, including increased efficiency and speed in grading, greater flexibility and accessibility for students, enhanced engagement through interactive formats, and the ability to personalize learning experiences.

UNIT 3.2

Analysis and interpretation of learning evidences, assessment data and measurement results

In this unit we will focus how to analyze data from students and learning process.

UNIT 3.2

Learning evidences and data

In HE, the assessment process is multifaceted and focuses on various types of learning evidence and data to evaluate student achievement and progress. List of the most important learning evidence and data categories for assessment purposes:

Each of them serves a unique role in providing a comprehensive picture of student learning and program effectiveness. Institutions and instructors can use a combination of direct and indirect evidence, along with course, program, and institutional data, to ensure robust assessment practices.

UNIT 3.2

Learning Analytics is the collection, analysis, and use of data related to student learning and academic activities to improve teaching and learning outcomes.

It involves applying data-driven techniques to understand and optimize the learning process by providing insights into student performance, engagement, and behavior.

It uses various types and sources of data and assessment results, to inform instructors about students' learning progress and achievements.

Tools for learning analytics

Several tools and platforms are used in HE to implement learning analytics. These tools help you to collect, analyze, and visualize student data.

Check bubbles for some of the most popular tools.

UNIT 3.2

Microsoft Power BI

Moodle Analytics

Tableau

IBM Watson Education

Canvas Analytics

Civitas Learning Platform

Brightspace Insights

UNIT 3.2

AI for assessment

AI is a useful tool for assessment, it automates and speeds up the assessment process and provides solutions to reduce tasks to take a significant burden off the instructor's shoulders. Take the following steps if you wish to use AI for assessment:

Design assessment objectives

Review and Reflect

Select AI tools

Monitor and Adjust

Prepare and Input Data

Implement AI in the Assessment Process

UNIT 3.2

Practical exercise

This practical exercise helps you to understand and effectively implement AI tools in the assessment process.

Instructions: 1. Read the provided use case scenario. 2. Answer the following questions based on the steps the instructor should take to integrate AI into the assessment process.

objectives, select appropriate AI tools, prepare and input relevant data, and integrate AI into the assessment process. The instructor will also need to continuously monitor AI performance and make necessary adjustments to ensure effective use. Finally, the instructor will review AI-generated insights to refine future assessments and instructional strategies.

Usecase: Integrating AI into Assessment for a Higher Education Course

Scenario: A HE instructor is implementing AI to enhance the assessment process for a course. The instructor aims to use AI tools to automate grading, provide personalized feedback, and analyze student performance data to improve learning outcomes. To achieve this, the instructor must design clear assessment

UNIT 3.2

Conclusions

A Multi-Stage Approach is Key to Leveraging AI in Assessment: Successfully integrating AI into assessment involves a structured process. This includes clearly defining assessment objectives, selecting appropriate AI tools, preparing and inputting relevant data, implementing AI in the assessment process, continuously monitoring and adjusting its performance, and finally, reviewing and reflecting on the outcomes to inform future practices.

Summary of the unit content

Digital Assessment Defined: Digital assessment leverages technology to evaluate student performance through various methods like online quizzes, assignments, and portfolios. It offers features like automated feedback, accessibility, and data-driven insights.

AI Can Streamline and Enhance Assessment: Artificial intelligence presents opportunities to automate and accelerate assessment processes, potentially reducing instructor workload. Thoughtful implementation, involving clear objective design, careful tool selection, data preparation, ongoing monitoring, and reflective review, is crucial for effective and fair AI-assisted assessment.

Learning Analytics Offers Data-Driven Insights: Learning analytics involves the systematic collection, analysis, and application of student learning data to enhance teaching and learning outcomes. Tools like Moodle Analytics, Canvas Analytics, Microsoft Power BI, and others help instructors track progress, identify patterns, and gain valuable insights into student performance and engagement.

UNIT 3.3

Effective feedback and support students to develop their learning practice

If we take the three central processes in assessments of making sure that: you are clear about where the learner is going; you are clear about where they are and you want to establish how to get there; and you think about the role of the teacher; the role of the other peers in the classroom and the learner themselves. You end up with five, what we call, key strategies. This unit focus how to use feedback for support students to develop their competences.

Dylan Wiliam (transcript from video)

UNIT 3.3

Feedback and motivation

Feedback is essential for motivation as it helps learners understand their progress, reinforces positive behaviors, and provides clear directions for improvement, fostering a sense of competence and autonomy (Hattie & Timperley, 2007).

Effective feedback encourages self-regulation and persistence by making goals more attainable and meaningful (Nicol & Macfarlane-Dick, 2006).

Feedback is specific and supportive boosting intrinsic motivation, leading to deeper engagement and better learning outcomes (Shute, 2008).

UNIT 3.3

21 tips for giving effective feedback

21 components of effective feedback each explanation in popwindow

tips 8-14.

tips 1-7.

tips 15-21.

UNIT 3.3

Reflective exercise

Feedback Development Exercise

Analyze the following feedback provided and identify which of the 21 components of effective feedback are being applied.

Usecase scenario: You are an instructor providing feedback to a student who has just completed a research project. The student has performed well but there are areas for improvement, particularly in the analysis and synthesis of information.

Feedback Statement

Feedback Statement

Feedback Statement

Feedback Statement

UNIT 3.3

Conclusions

A Multifaceted Approach to Feedback Delivery is Optimal: To maximize the impact of feedback, it should be delivered in appropriate amounts, be tied to action plans, and ideally come from multiple sources and in various forms (including data visualizations). Crucially, effective feedback is tailored to the individual learner, easy to understand, specific to their performance, and collaborative, encouraging the learner's input and solutions.

Summary of the unit content

Feedback is a Cornerstone of Motivation and Learning: Effective feedback is not just about pointing out errors; it's a powerful motivator that helps learners understand their progress, reinforces positive actions, and provides clear pathways for improvement. This, in turn, cultivates feelings of competence and autonomy, which are vital for engagement.

High-Quality Feedback Fosters Self-Regulation and Deeper Learning: When feedback is specific, supportive, and timely, it empowers learners to take ownership of their learning. By making goals clearer and more achievable, it encourages self-reflection, persistence, and a deeper engagement with the learning material, ultimately leading to better learning outcomes.

Effective Feedback Has Specific Characteristics: Providing impactful feedback involves more than just saying "good job" or "needs improvement." It requires being specific, timely, appropriate, focused on behavior (not personality), proactive, descriptive, non-judgmental, and based on accurate information. Furthermore, it should be recurring, embedded in the learning culture, linked to learning outcomes, and guiding towards action plans.

cASE STUDy

Better, faster: cutting-edge online assessments in MSD Every year, the Medical Science Division's Learning Technologies (MSDLT) team supports teaching staff to run more than 160 online assessments for over 17,000 participants - everything from quizzes and open-book tests to assessments sat under exam conditions, including formal University exams. But it's not just this scale and reach that's impressive. Online assessments can also be incredibly rich, incorporating audio, video, simulations and visualisations to put students through their paces. And they can be versatile enough to process algebra and other complex mathematical elements. Link to case study:

Better, faster: cutting-edge online assessments in MSD

Resources

Redecker, C., & Johannessen, Ø. (2013). Changing Assessment—Towards a New Assessment Paradigm Using ICT. European Journal of Education, 48(1), 79-96.

Kearney, S., Perkins, T., & Mak, A. (2020). Digital assessment: designing for student success. Australasian Journal of Educational Technology, 36(2), 67-79.

Astin, A. W. (2012). Assessment for excellence: The philosophy and practice of assessment and evaluation in higher education. Rowman & Littlefield Publishers.

Redecker, C. (2017). European Framework for the Digital Competence of Educators: DigCompEdu." Publications Office of the European Union.

Dringó-Horvath, I. M. Pinter, T. (Eds.) (2021). Educational technology in higher education, methodological considerations. Károli Gáspár University.

EUSurvey - Survey (europa.eu)

Hattie, J., & Timperley, H. (2007). The Power of Feedback. Review of Educational Research, 77(1), 81-112.

Shute, V. J. (2008). Focus on Formative Feedback. Review of Educational Research, 78(1), 153-189.

Jisc. (2021). Transforming assessment and feedback with technology. Jisc.org.uk

Resources

Delivering Great Feedback Infographic - Infographic Transcript (mindtools.com)

Nicol, D. J., & Macfarlane-Dick, D. (2006). "Formative assessment and self-regulated learning: A model and seven principles of good feedback practice." Studies in Higher Education, 31(2), 199-218.

Secolsky, C., & Denison, D. B. (Eds.). (2017). Handbook on measurement, assessment, and evaluation in higher education. Routledge.

Moodle analytics

Canvas analytics

Microsoft Power BI

IBM Watson Education

21 Components of Effective Feedback Infographic - e-Learning Infographics (elearninginfographics.com)

https://award.profformance.eu/search/readDetail/322

Wan, Ng (2015). New digital technology in education. Springer

Civitas Learning Platform

Tableau

https://www.youtube.com/watch?v=y5As7zVDzRQ (4:27)

Brightspace Insights

https://www.youtube.com/watch?v=_ZbgBukwD2c (2:43)

GLOSSARY

Digital technologies and tools for assessment refer to a wide-range of digital platforms, software, and applications designed to facilitate the evaluation of learning, performance, or skills in various settings. They include online quizzes, electronic surveys, e-portfolios, learning management systems (LMS), and AI-driven analytics that provide real-time feedback and enable personalized learning. They aim to streamline assessment processes, support diverse learning needs, and provide data-driven insights for improved educational outcomes.

Learning evidence refers to any documented demonstration of student knowledge, skills, or competencies that can be used to assess progress toward learning outcomes. Learning data encompasses quantitative and qualitative information collected through various tools and methods that provide insights into student learning behaviors, engagement, performance, and outcomes.

Assessment is an organic part of the entire educational process and provides information that measures its goals and content, the teaching and learning process, and the performances of the learner, while contributing to a more efficient organisation of teaching and learning from the perspectives of both instructors and students alike.

Digital technologies and tools for assessment

Learning evidence and data

Assessment

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GLOSSARY

The goal of formative assessment is to monitor student learning to provide ongoing feedback that can be used by instructors to improve their teaching and by students to improve their learning, to help them identify their strengths and weaknesses and target areas that need work and to help teachers recognize where students are struggling and address problems immediately. The goal of summative assessment is to evaluate student learning at the end of an instructional unit by comparing it against some standard or benchmark. See more:

Effective feedback is information provided to learners about their performance that is specific, timely, and constructive, aimed at guiding future improvement and learning. It should be clear and actionable, focusing on strengths and areas for development while promoting self-regulation and motivation, considering the learner's context and needs.

Digital assessment involves the use of digital technologies and tools that can enhance existing assessment practices and facilitate the collection of learning evidence and data to better support and assess learners, while enbling them to reflect and adapt the teaching and learning process and practice.

Formative and summative assessment

Digital assessment

Effective feedback

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GLOSSARY

Learning evidence refers to any documented demonstration of student knowledge, skills, or competencies that can be used to assess progress toward learning outcomes. Learning data encompasses quantitative and qualitative information collected through various tools and methods that provide insights into student learning behaviors, engagement, performance, and outcomes.

A wide-range of digital tools can be used for different assessment purposes, which provide data on usage of learning materials, research and consumption of information, communication and collaboration with peers, content creation and presentation, reflection and assessment of what has been learned.

Digital technologies for assessment embrace any products or services of relevant tools providing evidence and data of the students’ learning process, options for analysis and more targeted feedback and support.

Learning evidence and data

Digital technologies for assessment

Digital tools for assessment

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GLOSSARY

Personalization of learning is an educational approach that tailors instruction, content, and learning experiences to meet the individual needs, interests, and learning styles of each student. It empowers learners by allowing them to progress at their own pace, choose relevant learning paths, and engage in ways that optimize their personal success and development.

Effective feedback is specific, timely, and constructive information provided to learners that helps them understand their strengths and areas for improvement, guiding them toward achieving their learning goals.

Self-regulated learning (SRL) refers to learning that is guided by metacognition (thinking about one's thinking), strategic action (planning, monitoring, and evaluating personal progress against a standard), and motivation to learn. For more see:

Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts for purposes of understanding and optimizing learning and the environments in which it occurs. For more go to:

Self-regulated learning (SRL)

Personalisation of learning

Learning analytics

Effective feedback

Final Quiz of the module

10

Course completed!

Acknowledgements

4. Feedback Statement: "Your project shows potential, but you need to improve your analysis. This is crucial for your grade."

Components applied:

Focused: Highlights the importance of improving analysis.

Appropriate: Positive and constructive tone.

Specific to the learner’s performance: Discusses how to enhance a specific part of the project.

Dartmouth College

Dartmouth College outlines the "9 Principles of Good Practice for Assessing Student Learning," which serve as a foundational framework for conducting assessments in higher education. These principles include aligning assessment with educational values, employing diverse methods to capture comprehensive student learning, and involving a wide range of stakeholders in the assessment process to foster continuous improvement.

Accessibility and flexibility

Digital assessments can be accessed remotely, allowing students to complete their assessments from various locations and at different times, depending on the assessment design.

Example:

Check the case from PROFFORMANCE database Developmental evaluation in the cooperative it provides learning process provides complex assesment including students self-reflection

Tableau

Overview

Tableau is a powerful data visualization tool to analyze and present learning data. It integrates with various databases and LMS platforms to generate visual reports on student performance, engagement, and outcomes.

Key Features

Interactive data visualizations, customizable dashboards, integration with multiple data sources, and drill-down analysis.

Design assessment objectives

Clearly define the learning outcomes and objectives that the AI will assess, ensuring alignment with course goals and standards. Specify the types of assessments (e.g., quizzes, essays, projects) and criteria for evaluation.

In this sourse you will get an overview how to....SHORT description of TA

Course-Level Data

Scores on assignments that provide detailed insight into specific areas of strength and weakness in student learning.

Assignment Grades

Attendance and Participation

Learning Management System (LMS) Analytics:

Engagement metrics that can correlate with student success and participation in the learning process.

Data on student engagement, such as time spent on resources, interaction with course materials, and completion rates for assignments or activities.

Review and Reflect

After the assessment, review AI-generated insights and reports to identify trends and areas for improvement. Use the findings to inform future assessments, instructional adjustments, and personalized learning paths for students.

Monitor and Adjust

Continuously monitor the AI’s assessment processes to ensure accuracy and fairness. Make adjustments based on the system’s feedback, refining algorithms or assessment criteria as needed to improve reliability and relevance.

Implement AI in the Assessment Process

Use AI to facilitate assessments, whether by automating grading, personalizing tests, or generating real-time feedback. AI can also analyze patterns in student performance to adjust difficulty levels or suggest resources.

Select AI tools

Choose AI-powered assessment tools that match your objectives, such as automated grading systems, plagiarism detection, or adaptive testing platforms. Ensure the tools can analyze relevant data and provide insightful feedback.

Microsoft Power BI

Overview

MS Power BI is a business analytics tool that can be customized for educational purposes. It allows you to aggregate data from multiple sources (e.g., LMS, student information systems) and create interactive reports and visualizations. Power BI enables tracking trends, analyzing student outcomes, and improving decision-making based on data.

Key Features

Advanced data visualization, real-time dashboards, data integration from various sources, and predictive analytics capabilities.

Direct Evidence of Student Learning

Scholarly Papers

Digital Portfolios

Examinations

Academic papers that assess critical thinking, research abilities, and mastery of subject content.

Includes midterms, finals, and other cumulative tests that assess students' understanding of course material.

A collection of student work over time that showcases progress, creativity, and mastery of specific skills.

Laboratory Reports

Quizzes

For STEM fields, these reports assess practical application of theoretical knowledge and experimental skills.

Performance Tasks

Regular short assessments that provide insight into student comprehension of specific topics.

These tasks assess students' ability to apply skills in real or simulated settings.

Hint: You harness the power of digital technology to deliver prompt, specific, and clear feedback to students, when appropriate. Through digital platforms and tools, you ensure that feedback is tailored to individual student needs, enabling targeted guidance for their learning journey.

I utilize digital technologies for diverse and appropriate assessments.

I create, critically analyse, and interpret digital data on student’s activities, performance and progress.

I use digital technology to provide timely, targeted and clear feedback to students.

I adapt learning practices and provide support according to the results generated using digital technologies.

If you want to learn more about your strengths and the areas where you can enhance the ways in which you use digital technologies for teaching and learning, click here.

Summative Assessment Tools

Summative assessments are typically used at the end of a learning period to evaluate overall achievement.

• Online testing platforms (e.g., ExamSoft, Survey Monkey, Respondus):

Secure online testing platforms used for high-stakes exams, etc.

• Project and case-based assessment Tools (e.g., Google Workspace, Microsoft Teams):

Platforms that allow students to work collaboratively on complex projects or case studies, often with integrated tools for submission, feedback, and grading.

• Annotation and Feedback Tools (e.g., Turnitin Feedback Studio, Hypothesis):

Tools that allow instructors to provide detailed feedback on written work or other submissions, often integrated with plagiarism detection.

These tutorials will help guide you think issues of creating an effective digital assessment strategy.

Ashley Finley on the Future of Assessment in Higher Education (3 minutes)

5 Formative Assessment Ideas(5 minutes)

Some critical issues in enabling impactful assessment(20 minutes)

• Harnessing the Power of AI: Transforming Assignments and Assessments in Higher Education

This video explores how AI can transform formative assessments in higher education, emphasizing the integration of AI in designing engaging and adaptive assessments

• Artificial Intelligence Tools in Higher Education: This tutorial introduces various AI tools and explains how they can be leveraged for different assessment tasks in higher education.

Flexibility and Accessibility

Students can take assessments from anywhere, which increases accessibility for those who may not be able to physically attend campus.

Data-driven insights

These assessments can generate detailed analytics on student performance, helping educators identify trends, gaps in knowledge, and areas that may need further attention.

8. Based on accurate and credible information: The feedback should be based on accurate information. Never use rumors as examples.

9. Recurring: Feedback should be recurring.

10. Embedded in the Culture: Foster an environment of continuous feedback and professional development.

11. Focused: Feedback should be channeled toward key result areas. Feedback should also be linked to learning outcomes.

12. Guiding: The information given to the learner should be used to either confirm or correct their performance.

13. Tied to an action plan: Learner should know exactly how to increase performance and what steps needed to take.

14. An appropriate amount: Too much feedback will overwhelm and confuse the employee. Too little feedback is not sufficient to elicit a change.

Automated feedback and scoring

Digital assessments often provide automated feedback and grading, allowing for quicker turnaround times and reducing the administrative burden on instructors.

Indirect Evidence of Student Learning

Focus Groups and Interviews

Reflective Essays, Journals, Blogs

Surveys and Questionnaires

Self-reported data from students regarding their perceptions, understanding of learning subjects, including course evaluations, etc.

Qualitative data from students about their learning experiences and perceptions of knowledge and competence development.

Students’ self-assessment of their learning, often reflecting on growth, challenges, and development.

Hint: By using the digital data and results of learning analytics, you improve your teaching and you support students to use the data to the development of their learning practices.

Engagement Data

Participation, involvement in, time spent with learning materials and activities, engagement and collaboration with peers.

Student Engagement with Course Material and Curricular Activities

Use of Academic Support Services

Digital Learning Analytics

Data on how often students access tutoring, writing centers, or other support resources.

Data collected from digital platforms to track and analyze student behaviors and learning patterns.

IBM Watson Education

Overview

IBM Watson Education provides AI-driven learning analytics solutions. It uses machine learning and natural language processing to provide insights into student performance, learning styles, and content engagement. Watson Education helps create personalized learning experiences based on data analysis.

Key Features

Predictive analytics, personalized learning pathways, natural language processing, and AI-driven insights.

Efficiency and Speed

Both teachers and students can save time by using digital assessment. Automatic assessment speeds up scoring and feedback, allowing teachers to focus more on designing learning experiences.

Environmentally Friendly

Digital assessments reduce the need for paper, making them a more sustainable option compared to traditional exams.

2. Feedback Statement: "Your analysis was superficial and did not meet the expected standard. Please refer to the guidelines."

Components applied:

Specific: Identifies a problem with the analysis.

Based on accurate and credible information: Refers to guidelines.

Not given using judgmental language: No clear evidence of judgmental language.

1. Specific: Feedback must be concrete and relate to a specific, measureable performance goal.

2. Timely: Learner must receive the feedback as close to the assessment as possible.

3. Appropriate: Feedback should be presented in a positive, tactful and non-threatening manner.

4. Focus on behavior, not personality: Always provide feedback that is based on behavior, not personality or characteristics unless absolutely necessary.

5. Proactive: Don’t delay or avoid providing feedback. Identify issues and provide feedback before they become problems or have a large impact on the company.

6. Given using descriptive language: Describing how the learner’s behavior impacts performance will help facilitate understanding.

7. Not given using judgmental language: Avoiding judgmental language will decrease the possibility that the learner will be defensive.

Hint: You gather valuable data on student engagement, learning outcomes, and areas of improvement by utilizing various digital tools and learning management system. Through careful analysis and interpretation of this data (learning analytics), you gain insights into individual student needs and adapt your teaching strategies accordingly. You explore how digital data can inform instructional decisions and promote personalized learning experiences tailored to student's unique requirements.

Canvas Analytics

Overview

Canvas LMS offers built-in analytics that allow instructors to monitor student performance and engagement in real-time. It includes data visualizations of student activity, grades, and assignment submissions, enabling educators to intervene early if students are falling behind.

Key Features

Interactive dashboards, grade distribution analysis, and customizable reports. Canvas also supports integrations with third-party analytics tools for enhanced data analysis.

Formative Assessment Tools

Formative assessments are used to provide ongoing feedback during the learning process.

• Quizzes (e.g., Quizlet, Socrative, Edmodo, Google Forms, Kahoot!):

These tools allow for quick, low-stakes assessments that help gauge student understanding in real-time.

• Polls and surveys (e.g., Mentimeter, Poll Everywhere):

Useful for gathering instant feedback on student understanding and opinions during lectures.

• Learning Management Systems (LMS) integrated quizzes (e.g., Canvas, Blackboard, Moodle):

LMS platforms often have built-in quiz tools that can be used for both formative and summative assessments.

• Peer and self-assessment tools (e.g., Peergrade, Peermark, Google Docs):

These tools allow students to evaluate their own or their peers’ work, which promotes reflection and critical thinking.

• LMS Discussion Tools:

Tools for facilitating and assessing online discussions, often used for asynchronous collaborative learning.

• Reflective Journals and Blogs (e.g., WordPress, Blogger):

Online platforms where students can regularly reflect on their learning experiences, which can be assessed for depth of reflection and personal growth.

• ePortfolios (e.g., Portfolium, Mahara, FolioSpaces):

Digital portfolios where students can compile and reflect on their work over a course or program, providing a comprehensive view of their learning progress. ePortolios can be also use for summative assessment.

Acknowledgements

Professional coordinators, advisers Vilmos Vass Szilvia Besze Adviser Daliborka Luketic Designer Szabina Gyurisán Horváthné Co-designers Linda Huszár Bianka Bozzay

Authors Jan Beseda Loboda Zoltán Horváth-Dringó Ida Reviewers Horváth-Dringó Ida Anca Greere

Personalized Learning

Digital assessments can be adaptive, adjusting the difficulty of questions based on student responses. This can create a more personalized learning experience tailored to individual needs.

Hint: You embrace a wide range of assessment formats and methodologies to promote diversity and ensure appropriateness for different learners and contexts. Through digital tools, apps and platforms, you create interactive assessments that allow students to demonstrate their understanding in various ways, such as multimedia projects, online quizzes, collaborative discussions, and virtual simulations. You apply flexible assessment strategy that values individual strengths, fosters creativity, and encourages active participation through the integration of digital technologies.

1. Feedback Statement: "You did a good job on the project overall, but the analysis section could use more depth."

Components applied:

Specific: Addresses a particular part of the project.

Guiding: Suggests improvement in a specific area.

Focused: Centers on a key aspect of the project.

Performance-Based Assessment Tools

These tools assess students’ ability to apply knowledge in real-world or simulated scenarios.

• Digital content creation and presentation tools (e.g., blogs, Padlet, presentation tools, word processing, worksheets, etc.):

Tools for creating and delivering digital content and presentations, allowing assessment of communication and presentation skills.

These tools emphasize teamwork and collective problem-solving as part of the learning process.

• Collaborative Learning Platforms (e.g., Padlet, Miro, Trello):

Tools that allow students to work together on group projects or shared boards, often with real-time collaboration features.

• Peer Review Systems (e.g., PeerMark, Peergrade):

Systems that allow students to give and receive feedback on assignments, supporting the development of evaluative and critical thinking skills.

• Discussion Boards and Forums (e.g., LMS Discussion Tools):

Tools for facilitating and assessing online discussions, often used for asynchronous collaborative learning.

Technology-enabled assessment

Digital assessment involves the use of digital tools, platforms, and software to evaluate students' academic performance. This can include online quizzes, assignments, exams, simulations, and digital portfolios

Vanderbilt University

Vanderbilt University offers a comprehensive guide on various assessment methods: self-assessment, peer assessment, essays, and exams. The guide emphasizes the importance of diverse assessment approaches to enhance reliability and improve overall student performance. It also discusses strategies for integrating these methods effectively into the teaching and learning process.

Engagement

Digital assessments featuring multimodality of representation can increase student engagement, making the assessment process interactive and enjoyable.

Versatility

Digital assessments can take various forms, offering various methods to assess student learning and understanding.

Diagnostic Assessment Tools

Diagnostic assessments help identify students' prior knowledge, strengths, and areas for improvement before instruction begins.

• Pre-Tests and Diagnostic Quizzes (e.g., LMS Quiz Tools, Socrative):

Short quizzes that assess baseline knowledge and help instructors tailor instruction based on student needs.

15. From multiple sources: In order to internalize the feedback and elicit change, learner should receive feedback from multiple sources (peers, etc.).

16. In many forms: Graphs and charts that track individual and group performance are imperative to the feedback process.

17. From data: Quantitative measures of performance data should be presented in a meaningful way and should be used as concrete examples.

18. Tailored to the recipient: The individual learner’s characteristics, level of performance and cognitive processing style should influence the type of feedback they receive.

19. Easy to understand: Feedback should be easy to understand and the employee should repeat back the information discussed.

20. Specific to the learner’s performance: Managers should not include factors that are beyond the control of learner in the feedback process.

21. Collaborative: Allowing learner to contribute to the feedback process and offer solutions will help them accept the feedback more readily.

Moodle Analytics

Overview

Moodle is a Learning Management System (LMS), that has integrated learning analytics capabilities. It provides data on student engagement, progress, and performance within courses. Instructors can track activities like course participation, quiz results, and resource usage to identify at-risk students and tailor interventions.

Key Features

Predictive analytics, custom reports, and visual dashboards for tracking student behavior and progress within Moodle courses.

Brightspace Insights

Overview

Brightspace provides analytics on student engagement, performance, and content usage. Instructors can use the data to personalize learning and offer targeted interventions to students.

Key Features

Predictive analytics, performance dashboards, customizable reports, and early alert systems.

Prepare and Input Data

Provide the AI system with the necessary data, such as previous assessment results, rubrics, and grading criteria. Ensure the data is clean, well-organized, and sufficient for the AI to process effectively.

Columbia University

Columbia University provides an assessment guide that focuses on evaluating student learning in alignment with institutional goals and mission statements. The guide emphasizes the importance of ongoing assessment practices and utilizing data to improve both student outcomes and educational programs.

Peer and Self-Assessment

Peer Assessment and Review

Self-Assessment

Assessment by fellow students, which provides a different perspective on the quality and effectiveness of learning.

Opportunities for students to reflect on their own learning, providing insight into their self-perception of skills and knowledge.

3. Feedback Statement: "To improve your analysis, focus on incorporating more detailed evidence and connecting it to your conclusions. Review the provided rubric for specific criteria."

Components applied:

Specific: Provides clear directions for improvement.

Timely: Implies a focus on the current project.

Guiding: Offers concrete steps to improve.

Tied to an action plan: Suggests reviewing the rubric for criteria.

Learning Analytics and Data Tools

These tools use data to assess student engagement, progress, and outcomes.

• LMS Analytics (e.g., Canvas Analytics, Blackboard Analytics):

Built-in tools that track student engagement, assignment submission patterns, and performance across courses.

• Learning Analytics Platforms (e.g., Civitas Learning, Brightspace Insights):

Advanced platforms that aggregate data from multiple sources to provide insights into student progress and inform institutional decision-making.

Data Analytics

Digital tools provide detailed insights into student performance, including metrics such as time spent on each question, patterns of incorrect answers, and overall trends. This data can help educators improve course design and delivery.

Civitas Learning Platform

Overview

Civitas Learning offers a comprehensive learning analytics tool focused on student success. It aggregates data from various institutional systems to provide insights into student behaviors, academic performance, and potential risks. The platform uses predictive analytics to identify at-risk students and recommend interventions.

Key Features

Predictive analytics, student success dashboards, intervention tracking, and real-time alerts for educators.

If you want to learn more about your strengths and the areas where you can enhance the ways in which you use digital technologies for teaching and learning, click here. ​ This self-assessment tool develped by the EU Joint Research Centre helps you reflect on your digital competence as a higher education teacher. The tool consists of 25 questions of self-reflection to give you feedback with suggestions and tips on how to improve your teaching.