The second group of graphs shows information on users/ beliefs about self-regulated learning, their self-reported knowledge about self-regulated learning, and their confidence to support their own students' self-regulated learning development. In short, the following graphs answer the following type of questions:

• To what extent do teachers in a particular country believe in the value of self-regulated learning for their pupils? (Beliefs)
• How much do teachers in a particular country report to know about self-regulated learning? (Knowledge)
• How confident do teachers in a particular country feel to support their students' self-regulated learning? (Confidence)

These questions can be answered both for self-regulated learning as a whole, for particular groups of self-regulated learning strategies (e.g. forethought strategies or motivational strategies), and for various specific self-regulated learning strategies (e.g. planning and self-reflection).

Curious to see what specific self-regulated learning strategies are covered by each phase of learning (forethought, performance, and self-reflection phase) or by each component (motivation, behavior, metacognition, and emotion)? The tMAIL mobile app offers a quick overview!

Note. During the tMAIL pilot period, teachers had to fill in 3 times 14 questions in order to assess their beliefs, knowledge and confidence to teach self-regulated learning. However, after the piloting period, this assessment is no longer mandatory. However, users will need to complete the assessment if they want to use particular features. Consequently, the information shown below will not be available for all app users. Read the tMAIL Manual for Data-Driven Policy for further explanation.

Whenever relevant, graphs are accompanied by a short explanation of what information is shown, why it is relevant, and how it could be used now or in the future.

SRL Metrics by category

1. What?

   It shows users' beliefs, knowledge, and confidence to teach self-regulated learning strategies that students can use before learning (forethought), during learning (performance), and after learning is finished (self-reflection). It also shows users' average orientation towards forethought, performance, and self-reflection strategies. The scores are based on teachers' self-assessment when completing the personalization/assessment for the first time.

2. Why?

   The information shown, can give answers to the following general questions:

   • To what extent do teachers in a particular country believe in the value of self-regulated learning before, during, or after learning/a task? (Beliefs)
   • How much do teachers in a particular country report to know about self-regulated learning before, during, or after learning/a task? (Knowledge)
   • How confident do teachers in a particular country feel to support their students' self-regulated learning before, during, or after learning/a task? (Confidence)
   • How are teachers in a particular country generally oriented towards self-regulating your learning before, during and after learning? (Average)

   The graph shows the same information as the next graph (SRL metrics by phase), but makes it easier to answer the following type of questions: In what phase do teachers see the most value for their students? What phase do teachers know the most about? What self-regulated learning phase do teachers feel least confident to support?

   The average bars show where - overall - most progress can be achieved: helping teachers to support students' self-regulated learning before, during or after learning?

3. Examples (now or in the future)

   Based on the 'Average bars', policy could decide to first target the self-regulated learning phase teachers are either most or least familiar with. If teachers show strong beliefs and interest in self-regulated learning, policy might decide to primarily invest in the phase where most progress is to be made. However, if teachers' beliefs about self-regulated learning are rather low, policy might better decide to first invest in the phases teachers are most familiar with. Once they start to better master this phase and get to see some results, it can become a step-up for improving their self-regulated learning support in the other phases. Read the Manual for more examples.

SRL metrics by phase

1. What?

   It shows users' beliefs, knowledge, and confidence to teach self-regulated learning strategies that students can use before learning (forethought), during learning (performance), and after learning is finished (self-reflection). It also shows users' average orientation towards forethought, performance, and self-reflection strategies (both beliefs, knowledge and confidence). The scores are based on teachers' self-assessment when completing the personalization/assessment for the first time.

2. Why?

   The information shown, can give answers to the following general questions:

   • To what extent do teachers in a particular country believe in the value of self-regulated learning before, during, or after learning/a task? (Beliefs)
   • How much do teachers in a particular country report to know about self-regulated learning before, during, or after learning/a task? (Knowledge)
   • How confident do teachers in a particular country feel to support their students' self-regulated learning before, during, or after learning/a task? (Confidence)
   • How are teachers in a particular country generally oriented towards self-regulating your learning before, during and after learning? (Average)

   The graph shows the same information as the previous graph (SRL metrics by category) but makes it easier to answer the following type of questions: How much do teachers believe in, know about, and are confident with teaching self-regulated learning before learning?

   The average bars show you where - overall - most progress can be achieved: teachers' beliefs, knowledge, or confidence to teach self-regulated learning?

3. Examples (now or in the future)

   Based on the 'Average bars', policy could decide what is most urgent to invest in: teachers' beliefs, knowledge or confidence? In addition to the information presented here, they should take into account other forms of information available to them. For example, from research it is known that teachers' beliefs are a crucial pre-condition for learning. Hence, before further investing in training programs that increase teachers' knowledge about self-regulated learning, teachers should believe in the value of self-regulated for their own students. Read the Manual for more examples.

SRL metrics by component

1. What?

   It shows users' beliefs, knowledge, and confidence to teach self-regulated learning strategies that students can use to self-regulate their motivation, behavior (concrete actions), meta-cognition, and emotions. It also shows users' average orientation towards self-regulating their motivation, behavior, meta-cognition and emotion. The scores are based on teachers' self-assessment when completing the personalization/assessment for the first time.

2. Why?

   The information shown, can give answers to the following general questions:

   • To what extent do teachers in a particular country believe in the value of self-regulating your motivation, behaviour, meta-cognition and emotion? (Beliefs)
   • How much do teachers in a particular country report to know about self-regulating your motivation, behaviour, meta-cognition and emotion? (Knowledge)
   • How confident do teachers in a particular country feel to support students' self-regulation of their motivation, behaviour, meta-cognition and emotion? (Confidence)
   • How are teachers in a particular country generally oriented towards self-regulating your motivation, behaviour, meta-cognition, and emotion? (Average)

   More specifically, it can answer the following type of questions: In what component do teachers see the most value for their students? What component do teachers know the most about? What component do teachers feel least confident to support?

   The average bars show where - overall - most progress can be achieved: helping teachers to support students' self-regulation of your motivation, behaviour, meta-cognition and emotion?

3. Examples (now or in the future)

   Based on the 'Average bars', policy could decide to first support teachers to teach their students to self-regulate the component teachers are either most or least familiar with. If teachers show strong beliefs and interest in self-regulated learning, policy might decide to primarily invest in the component where most progress is to be made. However, if teachers' beliefs about self-regulated learning are rather low, policy might better decide to first invest in the components teachers are most familiar with. Once they start to better master this component and get to see some results, it can become a step-up for improving their self-regulated learning support of the other components. Read the Manual for more examples.

SRL metrics by topic

1. What?

   It shows users' beliefs, knowledge, and confidence to teach 14 specific self-regulated learning. It also shows users' average orientation towards specific self-regulated learning strategies. The scores are based on teachers' self-assessment when completing the personalization/assessment for the first time.

2. Why?

   The information shown, can give answers to the following general questions:

   • To what extent do teachers in a particular country believe in the value of specific self-regulated learning strategies? (Beliefs)
   • How much do teachers in a particular country report to know about specific self-regulated learning strategies? (Knowledge)
   • How confident do teachers in a particular country feel to support specific self-regulated learning strategies? (Confidence)
   • How are teachers in a particular country generally oriented towards specific self-regulated learning strategies? (Average)

   More specifically, it can answer the following type of questions: How much do teachers believe in, know about, and are confident with teaching each of the 14 specific self-regulated learning strategies?

3. Examples (now or in the future)

   Based on the 'Average bars', policy could decide to first support teachers to teach their students to self-regulate the SRL topic (e.g. planning) teachers are either most or least familiar with. If teachers show strong beliefs in self-regulated learning overall (See graph 'SRL metrics by phase', average beliefs bar), policy might decide to primarily invest in the SRL topic where most progress is to be made. However, if teachers' overall beliefs about self-regulated learning are rather low, policy might better decide to first invest in the SRL topics teachers are most familiar with. Once they start to better master this component and get to see some results, it can become a step-up for improving their self-regulated learning support of the other components. Read the Manual for more examples.

SRL metrics by category/country

1. What?

   It shows users' overall beliefs, knowledge, and confidence to teach self-regulated learning per country. The average bar shows teachers' overall orientation towards self-regulated learning (average of beliefs, knowledge, and confidence). The scores are based on teachers' self-assessment when completing the personalization/assessment for the first time.

2. Why?

   The information enables a transnational comparison of users' overall orientation towards self-regulated learning, as well as their beliefs, knowledge and confidence to teach it. It can give answers to the following general questions:

   • To what extent do teachers in a particular country believe in the value of self-regulated learning? (Beliefs)
   • How much do teachers in a particular country report to know about self-regulated learning? (Knowledge)
   • How confident do teachers in a particular country feel to support self-regulated learning? (Confidence)
   • How are teachers in a particular country generally oriented towards self-regulated learning? (Average)

   Note! Since the value of the information depends on the number of users, please check the number of users per country by clicking the country filtering box at the left-hand corner of the graph.

SRL metrics by phase/country

1. What?

   It shows users' overall orientation towards self-regulated learning strategies used before, during, and after learning per country. The average bar shows teachers; overall orientation towards self-regulated learning. The scores are based on teachers; self-assessment when completing the personalization/assessment for the first time.

2. Why?

   The information enables a transnational comparison of users' orientation towards self-regulated learning before, during and after learning. It can give answers to the following general questions:

   • How are teachers in particular countries oriented towards supporting students' self-regulated learning before learning?
   • How are teachers in particular countries oriented towards supporting students' self-regulated learning during learning?
   • How are teachers in particular countries oriented towards supporting students' self-regulated learning after learning?
   • How are teachers in particular countries generally oriented towards self-regulated learning? (Average)

   Since the value of the information depends on the number of users, please check the number of users per country by clicking the country filtering box at the left-hand corner of the graph.

SRL metrics - updated

The third group of graphs repeats some of the information shown above, but based on users' reassessment of their beliefs, knowledge, and confidence to teach self-regulated learning. It can show potential evolution in users' orientation towards self-regulated learning.

How does is work?

When teachers finish a particular course, they are asked to reassess their beliefs, knowledge and confidence related to that particular course. Since this reassessment is not mandatory, the graphs are currently based on a limited number of users only.

How to interpret?

As long as the number of users who take the reassessment is limited and reassessment does not become an integral part of the mobile training, interpretation and usability is very limited. However, the graphs are intended to show the future potential of monitoring the impact of the mobile training on users' beliefs, knowledge, and confidence to teach self-regulated learning.

If policy makers wish to collect and use this information, future policy action is necessary. Read the tMAIL Manual for Data-Driven Policy for further explanation.

By comparing the following two graphs with the graphs based on the initial assessment (when first completing the personalisation part), monitoring any potential impact becomes possible.

SRL metrics by category - updated

1. What?

   It shows users' beliefs, knowledge, and confidence to teach self-regulated learning strategies that students can use before learning (forethought), during learning (performance), and after learning is finished (self-reflection). It also shows users' average orientation towards forethought, performance, and self-reflection strategies (both beliefs, knowledge and confidence). The scores are based on teachers' reassessment of the questions answered when first opening the app.

2. Why?

   For more information on why and how this information can be used, have a look at the graph 'SRL metrics by category' above. By comparing both graphs, you can look for potential changes in teachers' beliefs, knowledge, and confidence to support students' self-regulated learning before, during, and after learning.

SRL metrics by phase - updated

1. What?

   It shows users' beliefs, knowledge, and confidence to teach self-regulated learning strategies that students can use before learning (forethought), during learning (performance), and after learning is finished (self-reflection). It also shows users' average orientation towards forethought, performance, and self-reflection strategies (both beliefs, knowledge and confidence). The scores are based on teachers' reassessment of the questions answered when first opening the app.

2. Why?

   For more information on why and how this information can be used, have a look at the graph 'SRL metrics by phase' above. By comparing both graphs, you can look for potential changes in teachers' beliefs, knowledge, and confidence to support students' self-regulated learning before, during, and after learning.