ABSTRACT
This chapter opens with a discussion of constructivism and constructivist instruction. Then this chapter discusses the variability of instructional apps implementing constructivist instruction. Since constructivist instruction engages learners in authentic tasks, this chapter simulates the work of an educational researcher, implementing machine learning techniques as tools for experimentation and knowledge discovery. Use of fictional data in the simulations assures privacy and works well to highlight the functionality of the instructional apps. The third section of this chapter provides guidance in implementing a machine learning technique to find patterns in data intended to improve instruction. This section provides a design specification, which identifies the target learners and the instructional objective. In addition, the design specification provides details important to instructional app development. The fourth section of this chapter simulates an educational researcher who seeks to discover a valid and reliable method for identifying effective K-12 teachers. This section provides a design specification, which identifies the target learners and the instructional objective. In addition, the design specification provides details important to instructional app development. Both the third and fourth sections also present exercises to refine the respective apps, which are provided to enhance skill to create instructional apps.
