BLOOM: Bringing the Life to an Overpolluted Oasis Mission, 2024
Deniz Celik, Wallace Pinto, Andrew Tompkin

Bloom is a web-based, single-player puzzle game designed to assess and enhance executive functioning (EF) skills. The player's goal is to return life to the uninhabitable planet by solving different puzzles. The game will allow the players to have their EF skills assessed according to their preferences. For each game level, there will be a description of how to play it and also which facet(s) of the EF skills can be improved by playing that level.

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This project outlines a digital game designed to assess and enhance executive functioning skills in elementary school students through engaging puzzle-solving activities. The game integrates a stealth assessment rooted in an evidence-centered design framework to assess and improve core executive functioning skills: working memory, inhibition, and cognitive flexibility. Players will navigate a variety of puzzles, each tailored to target specific EF sub-facets.

What is executive functioning (EF)?

EF skills are a group of top-down mental processes essential when concentration and attention are required (Diamond, 2013).
EF skills are essential for regulating higher-level cognitive processes such as sequencing, planning, decision-making, reasoning, and problem-solving (Cristofori et al., 2019; Miyake et al., 2000).

Stealth assessment and ECD

The aim of this project is to develop a digital game for the formative assessment of EF skills of elementary school students based on the stealth assessment framework (Shute, 2011; Shute, 2023; Shute & Rahimi, 2021). It is vital to accurately measure EF skills to design games that effectively foster these abilities, and stealth assessment (Shute, 2011) provides an innovative solution by employing evidence-centered design (ECD; Mislevy, Almond, & Lukas, 2003) to evaluate cognitive skills unobtrusively. There are four main theoretical models in the ECD framework: competency (CM), evidence (EM), task (TM), and assembly (AM) models (for the definition of each model, see Mislevy et al., 2003).

Competency Model (CM)

The CM outlines the knowledge and skills to be assessed. In our stealth assessment, we decided to use Diamond’s (2013) componential approach. Diamond’s model proposes a hierarchical structure of EFs with working memory and inhibition facets at the core level, and cognitive flexibility as a product of both facets (Diamond, 2013; Gray, 2017). We focused on the core EFs, and not on the higher-level EFs—such as Reasoning, Problem-Solving, and Planning. Once we defined our CM, we wrote some claims (inferences) that we wish to make about the students (players) that will be assessed with Bloom.

Evidence Model (EM)

In our case, Bloom will consist of different observables, such as the accuracy of recalling sequences of objects or words, and how long the player can balance multiple values that change over time. Game observables also include aspects such as play duration for focused attention, and how different each puzzle is from the previous one for task shifting. We created rubrics for each subfacet to score observables correctly.

Example of observables rubric

Task Model (TM)

In this model, we designed tasks the students should complete in the game. BLOOM consists of five different task types,

Visual-Spatial Working Memory (Card matching puzzle)
Verbal Working Memory (Text entry puzzle)
Inhibition at the level of attention (Juggling Puzzle)
Develop Alternative Strategies (Freeform drawing puzzle)
Task Shifting (Adjust dial puzzle)

Assembly Model (AM)

In this model, we designed the Q-matrix, and it serves as a tool to connect observables—elements associated with tasks or task families—to specific competencies. It is structured such that rows represent observables while columns represent competencies, with a binary system (1 or 0) indicating whether an observable evidences a particular competency. Additionally, we design the delivery mechanism of bloom which is the adaptive approach.

Example of Text-Entry Puzzle

Delivery mechanism example