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Last updated on 2024年9月23日

How do you analyze and report student feedback data to inform decision-making and quality assurance?

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Student feedback is a valuable source of information for higher education administrators who want to improve the quality of teaching and learning, student satisfaction, and institutional performance. However, collecting, analyzing, and reporting student feedback data can be challenging, especially when dealing with large and diverse student populations, multiple sources and formats of feedback, and complex quality assurance frameworks. In this article, you will learn how to analyze and report student feedback data to inform decision-making and quality assurance in higher education administration.

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1 Define your purpose and scope

Before you start analyzing and reporting student feedback data, you need to define your purpose and scope. What are the main questions or objectives that you want to address with the data? Who are the intended audiences and stakeholders for the data? How will the data be used to inform decision-making and quality assurance processes? These questions will help you determine the scope of your analysis and reporting, such as the level of detail, the time period, the comparison groups, and the key indicators that you want to focus on.

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Sonia Whiteley

CEO & Co-Founder | Genuine research insights. No BS.
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Let's back up a step and consider a student-centred model of student feedback. Students almost always say to me that they provide feedback so that their concerns can be addressed and situations improved. They often expect feedback to be actioned while they are still studying the course. And they want to be informed about the improvements and changes that have been made. People wonder why response rates to student feedback surveys are declining. A big part of the reason is that most feedback exercises don't put the student first. Students feel like they are providing feedback that goes nowhere - so why bother?!? Quality assurance activities and decision-making need to happen after we have taken care of the students' concerns.

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Kelly Wesener Michael, EdD

Strategic, innovative, solutions-oriented leader. Over 15 years higher education executive leadership experience - Faculty member and educator- Collaborative colleague - Green Bay Packer fan
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First and foremost, determine what data would be most meaningful, measurable, and manageable. We need to (1) ask the right questions, (2) to an appropriately defined audience, (3) using a method that provides data that we can effectively and accurately analyze and utilize.

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Manali Bhojwani

Strategic HR Innovator I Versatile HR Practitioner I Empowering Organizations with Human-Centric Strategies I Sarv.com I X Prudent Technologies & Consulting l X Capgemini l X Systweak Software
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Administer a post-course survey with quantitative (Likert scale) and qualitative (open-ended) questions.Promote the survey across platforms and ensure anonymity.Clean and categorize responses into themes.Calculate average satisfaction scores and compare across courses.Identify recurring themes in open-ended responses, such as requests for more hands-on learning opportunities.Summarize insights from quantitative and qualitative analyses.Create a visually appealing report with graphs and key takeaways.Suggest implementing more practical exercises based on student requests.Present findings to faculty and administration, encouraging discussion on action steps.Conduct follow-up surveys to assess the impact of changes made based on feedback.

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2 Collect and organize your data

The next step is to collect and organize your data from various sources and formats. Depending on your purpose and scope, you may need to gather data from surveys, focus groups, interviews, course evaluations, student records, learning analytics, or other sources. You may also need to convert qualitative data into quantitative data, or vice versa, to facilitate analysis and reporting. To organize your data, you may use software tools such as spreadsheets, databases, or statistical packages, or create your own data management system. You should also ensure that your data is accurate, complete, reliable, and ethical.

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Ashtyn Davis, M.Ed.
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I worked on an assessment project while at the University of Colorado-Boulder in looking at student staff (RA) training related to trauma in the RA role, and our conversations revolved around: why are we asking the questions we were asking, and most importantly, what are we trying to get out of the survey. For instance, one wouldn't ask what is your favorite color if we were doing a program assessment. While assessing the program at the State Department, we used a mix of qual and quantitative questions and included an optional section at the end if people wanted to include their email for a follow-up exit interview via Zoom/Teams.

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3 Analyze and interpret your data

Once you have collected and organized your data, you can start analyzing and interpreting your data. Depending on your purpose and scope, you may use different methods and techniques to analyze your data, such as descriptive statistics, inferential statistics, trend analysis, gap analysis, correlation analysis, factor analysis, or thematic analysis. You should also interpret your data in relation to your research questions or objectives, as well as the relevant literature, benchmarks, standards, or best practices. You should also identify the strengths, weaknesses, opportunities, and threats of your data, as well as the limitations and assumptions of your analysis.

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4 Report and communicate your data

The final step is to report and communicate your data to your audiences and stakeholders. Depending on your purpose and scope, you may use different formats and media to report and communicate your data, such as tables, charts, graphs, dashboards, reports, presentations, or infographics. You should also use clear, concise, and consistent language and terminology to convey your data. You should also highlight the main findings, conclusions, and recommendations of your analysis, as well as the implications and actions for decision-making and quality assurance.

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Rebekah Paré

Career services consultant & strategist for higher ed leaders ??| Driving 21st-century career innovation & student success metrics?
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Communicate back to students what you learned from them and how their input/feedback will be utilized to make improvements. Students are our most important stakeholders, and when we involve them in reviews and program designs, we should make sure to reflect back to them that their contributions matter. Consider it part of the education process and excellent modelling for their future careers.

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Ashtyn Davis, M.Ed.
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Some things to think about may include: 1) What does the audience care to know about; and what does that information mean to them? 2) What is the easiest way to share data? We want people to learn about the data in a simple, yet easy way to understand the data. How I present the data to student staff versus our Executive Director will be incredibly different, because of their stakeholdership value in the organization.

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5 Follow up and evaluate your data

After you have reported and communicated your data, you should follow up and evaluate your data. You should monitor and assess the impact and outcomes of your data on decision-making and quality assurance processes, such as changes in policies, practices, or performance. You should also solicit and incorporate feedback from your audiences and stakeholders on the quality and usefulness of your data, as well as the areas for improvement. You should also review and update your data collection, analysis, and reporting methods and tools, as well as your purpose and scope, to ensure that they are relevant and effective.

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6 Learn and improve from your data

The final step is to learn and improve from your data. You should use your data as a source of learning and improvement for yourself, your team, your department, or your institution. You should identify the best practices, lessons learned, and success factors of your data analysis and reporting, as well as the challenges, gaps, and risks. You should also share and disseminate your data and insights with other higher education administrators, practitioners, or researchers who may benefit from them. You should also seek and engage in professional development opportunities to enhance your skills and knowledge on data analysis and reporting.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Ashtyn Davis, M.Ed.
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Talk to others in formal and informal settings. Ask them how are they doing, check in with them, and how are/were their experiences. If we care about quality assurance, then we also need to care about people's experiences and ensure that, especially with how expensive it is to be in higher education, they are getting their money's worth in our system. Higher education is the last place where we need subpar work.

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JULIANA GUEDES ARVELOS BARBOSA

Consultora Educacional e Especialista em Gest?o Estratégica: Desenvolvendo Carreiras e Otimizando Processos Educacionais
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Comece organizando os dados de forma sistemática, identificando padr?es e áreas que precisam de aten??o. Em seguida, compartilhe essas informa??es com a equipe, promovendo discuss?es sobre possíveis a??es e melhorias. é importante que esse processo seja transparente e que os alunos vejam como seu feedback está sendo utilizado, o que n?o apenas fortalece a confian?a, mas também incentiva uma cultura de participa??o ativa e colabora??o na melhoria contínua.

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How do you analyze and report student feedback data to inform decision-making and quality assurance?

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1 Define your purpose and scope

2 Collect and organize your data

3 Analyze and interpret your data

4 Report and communicate your data

5 Follow up and evaluate your data

6 Learn and improve from your data

7 Here’s what else to consider

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