Identifying elementary students' pre-instructional ability to develop algorithms and step-by-step instructions

Abstract

The desire to expose more students to computer science has led to the development of a plethora of educational activities [16,7,15,4] and outreach programs to broaden participation in computer science. Despite extensive resources (time and money), they have made little impact on the diversity of students pursuing computer science. To realize large gains, computational thinking must be integrated into K-12 systems, starting with elementary school. In order to do so, existing resources need to be adapted for a school setting.In order to make a curriculum with lessons that build on each other over several years, and accountability for student learning, we need standards, an understanding of how students learn, and identification of what students know before exposure to the curriculum.In this paper, we present our detailed findings of what fourth graders know before encountering a computational thinking curriculum. Groups of students participated in activities modified from CS Unplugged [4] in order to discover their knowledge (rather than provide instruction). We identify aspects of the activities students were able to complete successfully, and where they will need further instruction. We then explain how we used these results to modify our pilot curriculum.

A K-8 Debugging Learning Trajectory Derived from Research Literature

“…Researchers have attempted to discover what CT concepts students use successfully at different ages [14,19,34]. In addition, several efforts have synthesized existing knowledge and research to guide future curriculum development.…”

Computational thinking curriculum development for upper elementary school classes

“…We also tested prior knowledge for our algorithms learning progression strand. We found that, with little to no instruction, students were able to create an algorithm for sorting six canisters and identified the limitations of their algorithms when scaled to a larger number of items [11]. The students also struggled with the distinction between speeding up the algorithm and speeding up its implementation, so we adjusted our curriculum to go over this distinction [11].…”

Beyond jam sandwiches and cups of tea: An exploration of primary pupils' algorithm‐evaluation strategies

“…In contrast, Dwyer, Hill, Carpenter, Harlow, and Franklin (2014) focus on the sequence of steps chosen to solve a problem efficiently. They must consist of a finite number of exact instructions, terminate after a finite number of steps when applied to an input, and produce a correct answer when instructions are followed correctly.…”

“…For instance, Misfeldt and Ejsing-Dunn (2015) refer to "systematic descriptions of problem-solving and construction strategies, cause-effect relationships, and events." In contrast, Dwyer, Hill, Carpenter, Harlow, and Franklin (2014) focus on the sequence of steps chosen to solve a problem efficiently. Furthermore, within her much cited definition of computational thinking, Wing (2011) refers to algorithm as "an abstraction of a process that takes inputs, executes a sequence of steps, and produces outputs to satisfy a desired goal."…”