What Teachers Should See in a Reading Dashboard

A teacher opens a reading dashboard to decide what to do next week. Many dashboards answer a different question: how much activity happened. This article sets out the four things a teacher needs to see each week in order to act. It reports what research on teachers' use of data has found, and what that means for the screen you look at. It ends with design rules that work for any dashboard, or for a spreadsheet you keep yourself, and a short weekly routine.

What should a teacher's reading dashboard show?

A teacher's reading dashboard should show four things for one class and one week: who has not read, who is stuck, which words are slipping, and which questions most pupils missed. Each answer should be a short list of names, words or questions. Each should point to something you can do on Monday.

• Who has not read. Pupils who have not finished this week's story, with the day they last read.
• Who is stuck. Pupils who finished but scored low on the check, or who started a story and stopped.
• Which words are not being kept. Words the class met in earlier stories and now gets wrong.
• Which questions most pupils missed. A question missed by most of the class is usually a teaching point, not a pupil problem.

This list is advice from practice. It follows from what formative assessment is for. Black and Wiliam (1998) define formative assessment as all the activities that provide information to be used as feedback to modify teaching and learning. A number that changes nothing next week is not doing that job.

School leaders need a different cut of the same record: totals by class, grade and term. How to Write a Term Reading Report for Your Board covers that view. This article is about the teacher's week.

What research on teachers' use of data has found

Schools have been asked to use data for many years. The research on how teachers actually use it is less confident than the policy.

Mandinach and Gummer (2013) note that policymakers require educators to use data to inform practice. Attention to building the human capacity to use data has not grown with that demand. They argue that educators need data literacy skills, and that schools of education offer few formal courses in them.

Datnow and Hubbard (2016) reviewed a decade of international research on teachers' capacity for, and beliefs about, data use. Efforts to build teachers' capacity often fell short of their goals. Teachers held varied beliefs about data, and some felt they lacked the ability to use it to inform instruction. The authors argue that data use should be decoupled from external accountability demands. It should also draw on a variety of information about pupils' learning.

Schildkamp (2019) describes data use as a cycle: define goals, collect data, make sense of it, take improvement actions and evaluate them. She notes that data use often focuses on summative assessment data, although many other sources are available. She names data literacy and leadership among the most important enablers and barriers.

Wayman (2005) adds a practical point. Student data are often stored in forms that are hard to access, manipulate and interpret. Those barriers keep data out of classroom decisions.

What this means for a dashboard

Read together, these studies suggest three things. This is our reading of them, not a tested finding. A screen cannot give a teacher data literacy, so it should do as much of the sense-making as it honestly can. Weekly class data should feel like a teaching tool, not an accountability check. And reading data should sit beside other evidence, such as what you heard in the lesson.

The class snapshot: four questions on one screen

The first screen a teacher sees should be their own class, this week. The table sets out what each question needs and what it can lead to.

Two notes on the table. First, show the day each pupil last read, not just a yes or a no. 'Last read Monday' and 'last read three weeks ago' call for different conversations. Second, 'stuck' needs two results, not one. A single low score can be a bad day.

Words slip for a reason, usually too few meetings. How Many Times Must a Learner Meet a Word? reviews the evidence on repetition.

Flags a teacher can act on

A flag is a line that tells you a pupil, a word or a question needs attention. A good flag names who or what, says what happened, and gives the evidence in plain words.

• Weak: 'Low engagement.' Strong: 'Sara has not opened a story since 12 March.'
• Weak: 'Comprehension risk.' Strong: 'Lina scored 2 of 6 and 3 of 6 on her last two A2 stories.'
• Weak: 'Vocabulary below target.' Strong: '18 of 26 pupils got borrow wrong this week, three weeks after meeting it.'

Keep flags few. A list of thirty flags gets skimmed, and the pupils who matter most are lost in it. Five names you can see this week are enough. This is practice, not a research finding.

Each flag should open the detail behind it in one step: the pupil's last stories, checks and answers. If you are new to a flag-based view, check that detail for the first few weeks. Trust the flags once they keep matching what you see in class.

That flag was about the class, not about one pupil. Seeing the question with its count is what made the lesson possible.

Design rules for any dashboard or spreadsheet

Research on dashboards is young. Schwendimann and colleagues (2017) reviewed 55 papers on learning dashboards. Most studies were exploratory or proof-of-concept. The authors call for longitudinal research in real settings, and for studies that systematically compare dashboard designs.

So the rules below are practice, drawn from the research on data use above. They apply to a spreadsheet as much as to a commercial product.

1. Open on one class and one week. School-wide views belong to leaders.
2. Show names and words, not only percentages. '23 of 26 read' should come with the three names.
3. Show the spread, not just the average. Put the number of pupils who read nothing beside the class average.
4. Compare each pupil with their own record. This week against last week tells you more than a rank in class.
5. Keep flags few, and give the reason for each.
6. Put the detail one step away. One click, or one tab of the spreadsheet.
7. Use the same layout every week. Changes make trends hard to see.
8. Drop any column nobody has acted on in a month.

Rule 4 also reflects Datnow and Hubbard (2016), who argue for separating data use from accountability pressure. Our reading is that a teacher's view should not double as a league table of pupils or classes.

What to leave off the teacher's view

Some numbers are easy to collect and hard to use. Leave them off the first screen, or leave them out.

• Logins and minutes online. They count time on a screen, not reading.
• School-wide totals. They hide every pupil inside them.
• Rankings of classes or teachers. They turn a teaching tool into a judgement.
• Every available metric at once. If a column needs a manual, it does not belong in the weekly view.

Pupil records need care too. A teacher should see their own pupils, not pupils they do not teach. Student Data Privacy: Questions to Ask an EdTech Vendor lists what to ask about who can see what.

A ten-minute weekly routine

A dashboard is only as useful as the habit around it. A weekly routine keeps the look short and the action concrete. The steps are a suggestion from practice.

1. Pick a fixed day and time, for example Friday after the last lesson.
2. Read the four questions in order and write down no more than five names.
3. Note three words and one question to revisit.
4. Choose one action for each name: a word with the pupil, an easier story, or reading time in class.
5. The next Friday, check whether those actions worked before you look at anything new.

A quick daily look can help near a deadline, but decisions belong in the weekly review. For the measures behind the snapshot, and how often each one changes, see How to Measure Reading Progress in a Language Program.

How iRead handles this

In iRead, every game clear and quiz answer feeds one progress record per word. Teachers see retention per word, per game and per class. Quiz questions are generated from the story itself: real sentences, the story's grammar, the plot and the moral. Attendance at sessions is recorded automatically, and individual student data is visible only to the school's own staff.

Key takeaway

Build the teacher's view around four weekly questions, and answer each with names, words or questions. Keep it short, keep it the same each week, and act on it.

Frequently asked questions

Sources

1. Mandinach, E. B., & Gummer, E. S. (2013). A systemic view of implementing data literacy in educator preparation. Educational Researcher, 42(1), 30-37. doi.org/10.3102/0013189X12459803
2. Datnow, A., & Hubbard, L. (2016). Teacher capacity for and beliefs about data-driven decision making: A literature review of international research. Journal of Educational Change, 17(1), 7-28. doi.org/10.1007/s10833-015-9264-2
3. Schildkamp, K. (2019). Data-based decision-making for school improvement: Research insights and gaps. Educational Research, 61(3), 257-273. doi.org/10.1080/00131881.2019.1625716
4. Wayman, J. C. (2005). Involving teachers in data-driven decision making: Using computer data systems to support teacher inquiry and reflection. Journal of Education for Students Placed at Risk, 10(3), 295-308. doi.org/10.1207/s15327671espr1003_5
5. Schwendimann, B. A., Rodríguez-Triana, M. J., Vozniuk, A., Prieto, L. P., Shirvani Boroujeni, M., Holzer, A., Gillet, D., & Dillenbourg, P. (2017). Perceiving learning at a glance: A systematic literature review of learning dashboard research. IEEE Transactions on Learning Technologies, 10(1), 30-41. doi.org/10.1109/TLT.2016.2599522
6. Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5(1), 7-74. doi.org/10.1080/0969595980050102