Secondary Outcomes (explanation)
1) Student performance on subskills
For mathematics, items are categorized as measures of either one of the following four abilities: Algebra; geometry; number system; and data/statistics. For science, items are categorized as measures of either biology, chemistry, or physics. In summary, this subskill analysis will establish the extent to which the program affected a student's probability of mastering each of these subskills.
In the case of subskills, because of the lower number of items per sub-skill, student performance will not be scored with a continuous measure of ability. Instead, I will distinguish between three categories of mastery, for each of the two subjects: students who have mastered grade-level appropriate material; students who have only mastered material from one and two years below their grade-level; and other students. I will determine students' level of mastery empirically, through a Cognitive Diagnostic Model (CDM).
2) Teaching behaviors and instructional quality
The program's effects on teaching behaviors and on instructional quality will be assessed through two instruments: Classroom observations and student reports. First, the program includes bi-weekly school visits and monthly classroom observations. All visits and observations will be conducted in intervention and control schools. For this purpose, the study developed an instrument to measure the program's effect on the quality of instruction a student receives. Secondly, during school visits, a subset of students will be surveyed on common classroom behaviors. The study explicitly defines either of these data sources as a measure of mechanisms, i.e. not as a main outcome.
Romero et al. employ a Lasso procedure to identify potential mediators (from a large number of variables). I will follow the authors' approach (ibid.) to identify mediating instructional behaviors; yet, the Lasso procedure will be forced to include teachers' use of ICT materials as a predictor. In turn, concerning instructional quality, I pre-specify six dimensions that will be investigated as potential mediators (monitoring of student learning; feedback; maximization of learning time; density of the mathematics / science; clarity of content and lack of errors; richness of the mathematics / science).
3) Intervention monitoring
Sign-in sheets will be used to track teachers' exposure to capacity-building activities. Avanti Fellows will moreover provide data from its software backend, to track teachers' use of videos and digital learning materials. Monitoring data will also be collected in the above-mentioned bi-weekly and monthly visits, through a structured school questionnaire.