The examples used in this study were created based on guidelines that reflect the
current status of research in instructional psychology and didactics of mathematics.
Furthermore, these examples were evaluated in several classes. Every example was
equipped with a bar of five interactive control-buttons (next step, skip step, step back,
still, reset).
Collecting and coding of video data
Every pair of students worked with a desktop-computer. No matter what kind of
material they processed (animated worked-out examples or other tasks in the workbook),
a camera on top of the computer-screen recorded the pairs’ behaviour during the
intervention. Simultaneously the screen was recorded. Both data were synchronized
and then coded with the usability testing software MORAE®.
The video data was coded on two levels. On the first one, all recordings were divided
into disjoint time intervals based on 21 categories. These periods classify the processed
task-form (worked-out-example, self-explanation prompt, incomplete example, task or
miscellaneous) and the students’ behaviour (quiet processing, content-related
dialogues with group-members, content-related dialogues with the teacher and
distraction). “Class instruction” constitutes another single category.
On the second level, the worked-out-example- and self-explanation-prompt-periods
were examined more specifically. Three main categories were coded with markers:
metacognition, self-explanations and reasoning. Three distinct sub categories for the
coding of metacognition were distinguished: planning, monitoring and regulation. The
self-explanations were divided into two categories: high self-explanations and
anticipation. For the analysis of reasoning three different categories were established:
describing mathematical facts, questioning of given facts and reasoning. The reliability
for both coding procedures exceeded 90%.
EXEMPLARY RESULTS
The collected data allow analyses on several levels. On the global level, the students’
prior knowledge and their productivity during the intervention phase can be estimated
by the pre- and post-test-results, the sum of all distraction-periods per class and the
spent time per example. Results of the pre- and post-test show significant increase in
learning in both classes. On a more specific level, analysing the time-intervals against
the background of the different task-forms or the different kinds of behaviour during
the processing of animated worked-out-examples or self-explanation prompts gives
hints for answering the research questions.
The examples used in this study were created based on guidelines that reflect thecurrent status of research in instructional psychology and didactics of mathematics.Furthermore, these examples were evaluated in several classes. Every example wasequipped with a bar of five interactive control-buttons (next step, skip step, step back,still, reset).Collecting and coding of video dataEvery pair of students worked with a desktop-computer. No matter what kind ofmaterial they processed (animated worked-out examples or other tasks in the workbook),a camera on top of the computer-screen recorded the pairs’ behaviour during theintervention. Simultaneously the screen was recorded. Both data were synchronizedand then coded with the usability testing software MORAE®.The video data was coded on two levels. On the first one, all recordings were dividedinto disjoint time intervals based on 21 categories. These periods classify the processedtask-form (worked-out-example, self-explanation prompt, incomplete example, task ormiscellaneous) and the students’ behaviour (quiet processing, content-relateddialogues with group-members, content-related dialogues with the teacher anddistraction). “Class instruction” constitutes another single category.On the second level, the worked-out-example- and self-explanation-prompt-periodswere examined more specifically. Three main categories were coded with markers:metacognition, self-explanations and reasoning. Three distinct sub categories for the
coding of metacognition were distinguished: planning, monitoring and regulation. The
self-explanations were divided into two categories: high self-explanations and
anticipation. For the analysis of reasoning three different categories were established:
describing mathematical facts, questioning of given facts and reasoning. The reliability
for both coding procedures exceeded 90%.
EXEMPLARY RESULTS
The collected data allow analyses on several levels. On the global level, the students’
prior knowledge and their productivity during the intervention phase can be estimated
by the pre- and post-test-results, the sum of all distraction-periods per class and the
spent time per example. Results of the pre- and post-test show significant increase in
learning in both classes. On a more specific level, analysing the time-intervals against
the background of the different task-forms or the different kinds of behaviour during
the processing of animated worked-out-examples or self-explanation prompts gives
hints for answering the research questions.
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