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Learning through Play: Behavioural Lens

This week we explore how we learn through a behavioural lens.

Learning through Play: Behavioural Lens
Image credit: Painting by Johann Sperl, kindergarten, around 1885
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Learning through play
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In 1971, a high school teacher named Don Rawitsch had a problem: his students were bored with history class. He needed a way to make learning about the past more exciting and relevant to his students. So he developed a computer game called The Oregon Trail, which was based on the experiences of real-life pioneers who travelled west in the 1800s. The success of the game demonstrated the effectiveness of using games as a fun and engaging teaching tool. This led researchers to further explore the impact of game-based learning on the learning process. With the integration of psychology, neuroscience, and sociology, behavioural science offers valuable insights into how individuals learn, acquire knowledge, and develop skills(Lavecchia et al., 2016).

How we learn:

Learning is a dynamic process that involves observation, experience, and education. It goes beyond simply memorising facts or repeating information mindlessly. Instead, learning requires active engagement with the material by making connections to previous knowledge and thinking critically about it.

Friedrich Fröbel, a German educator who introduced play-based learning in early childhood education through 'Kindergarten', understood this concept well. He developed innovative educational materials called "gifts," including building blocks which later became the inspiration for the iconic LEGO bricks we know today. These materials allowed children to explore, manipulate, and create, fostering hands-on learning experiences that sparked curiosity and creativity.

Image credit: Fröbel Building Blocks

Research on learning distinguishes between two fundamental approaches: deep and surface learning (Marton & Säljö, 1979). Deep learners aim to understand the material thoroughly, going beyond the surface to connect it with their prior knowledge, structure ideas, and critically evaluate the information presented. In contrast, surface learners predominantly rely on memorization as their learning strategy. Importantly, it's essential to recognise that deep and surface learning are not inherent personal characteristics but are influenced by the learning environment (Biggs et al., 2001).

Image credit: Hattie and Donoghue (2016)

Building upon this foundation, research has revealed that learning comprises distinct stages, each with its unique characteristics and challenges. Hattie and Donoghue (2016) introduced a model based on a synthesis of 228 meta-analyses, suggesting that different learning strategies are effective at specific stages of the learning cycle. The initial stage is acquisition, where individuals encounter and encode new information or skills (Schunk, 2012). This phase lays the groundwork for subsequent learning phases. Following acquisition, the consolidation phase comes into play, involving the solidification of knowledge through repetition and practice (Roediger & Karpicke, 2006). Repetition serves to embed information into long-term memory. The subsequent stage, transfer, entails the application of acquired knowledge or skills in novel contexts (Perkins & Salomon, 1992). It is during this phase that learners demonstrate their ability to adapt and utilise what they've learned beyond the initial context. Finally, metacognition, characterised by evaluating one's learning and promoting self-regulation (Flavell, 1979), plays an integral role. Here, individuals reflect on their learning process, enhancing their ability to monitor and adjust their approach for more effective learning. The iterative cycles of design, testing, and refinement in this framework reinforce the value of failures as an integral part of the learning process (Penuel & Gallagher, 2009).

Importantly, the model emphasises that educators should prioritise learning over grades and equip students with learning strategies and skills. It encompasses three dimensions: skill (knowledge and ability), will (student dispositions affecting learning), and thrill (motivation, emotions, and enjoyment of learning). This perspective underscores that learning and achievement are related rather than opposing concepts.

In addition, student motivation emerges as a pivotal factor. Intrinsic motivation, characterised by internal drive and genuine interest, often leads to enhanced performance and better retention. It fuels the learning engine, motivating individuals to engage more deeply with the material. Additionally, emotions, engagement, attitudes, and personal experiences also play a crucial role in the learning process (Harju et al., 2019). These factors influence the learner's level of interest, attention, and overall cognitive engagement, ultimately impacting the encoding and retention of information.

However, despite the potential of these positive factors to facilitate learning, there are also obstacles and cognitive biases that can hinder or impede the learning process. Drawing from principles in behavioural economics (Lavecchia et al., 2016), four key barriers to effective learning can be identified:

  1. Tendency to overfocus on the present, which may cause students to disregard the long-term benefits of education (Present Bias).
  2. Overreliance on routine and exclusion of non-salient information, which could hamper exposure to new learning methods and opportunities (Salience Bias).
  3. Overemphasis on negative identities, likely leading to low self-esteem and a lack of confidence, which could affect the learning process and outcomes (Identity Bias).
  4. Making mistakes due to lack of information or too many options, complicates decision-making around educational choices (Choice Overload).

To address these barriers, we can explore the use of design-based learning tools. These tools allow designers to make choices within a controlled and supportive design environment, where they can experiment, learn from their decisions, and understand the consequences of their design choices.

Why Student agency matters in learning:

Only learners can learn — teachers cannot learn for them, or “make” them learn.

- Prof. Jean Lave, Social Anthropologist, Learning as a Socially Situated Activity

Student agency, or the active participation and ownership of learning by students themselves, is crucial for effective learning. They are not passive recipients of knowledge, but rather active participants who make choices, set goals, and take actions to acquire knowledge and develop skills. Research shows that when students feel a sense of agency in their learning, they are more likely to be motivated, engaged, and persistent in pursuing their educational goals. Various studies, such as by Bush et.al.,(2011), Luo et.al.,(2019), and Stenalt et.al., (2021), highlight the positive impact of student agency on learning. They found benefits in skills application, problem-solving, effect during design-based learning, and superior performance in classrooms.

In the broader educational landscape, design-based learning tools have shown their effectiveness, with notable examples even emerging from India.

In 1999, a groundbreaking experiment in a New Delhi slum left a computer with no instructions. Remarkably, children quickly taught themselves to surf the web. This project called the Hole in the Wall project, was repeated in 23 locations, emphasizing children's natural tech-learning abilities despite language and education barriers. It underscored the significance of student-driven learning and greatly enhanced computer literacy in rural Indian children from various backgrounds. (Mitra, 2005).

Image credit: Hole in the Wall Project

Atal Tinkering Labs (ATLs) play a crucial role in promoting collaboration and creativity. They empower students to address societal issues and drive meaningful changes. According to Yadav et al. (2023), ATLs have successfully nurtured innovation and entrepreneurship in schools. Through internal tinkering and innovation projects, ATL students not only present their creations but also interact with peers and parents from non-ATL schools, making ATLs vibrant centers of creativity. This supportive environment not only encourages innovation but also prepares students to promote their ideas externally, gaining recognition and support.

Image credit: Atal Tinkering Labs

In 2010, Mindspark, a computer-assisted learning (CAL) software program, was introduced in Rajasthan by JPAL. It offers personalized instruction using interactive games, videos, and activities based on high-quality materials. It assesses students continuously and provides detailed feedback. Mindspark uses data to tailor content to each student's learning level and adjusts dynamically to their progress. It's versatile, working on various devices, online or offline, for classroom, after-school, or self-guided study. This experiment is renowned for its educational impact and has been adapted to many schools in the country(Cole et.al.,2017).

Image credit: Mindsparks

In 2014, Abhijit Sinha's Project DEFY popularized the idea of teacher-less schools. This project transformed Banjarapalya village near Bengaluru into a tech-savvy community with "Nooks" for internet access and self-directed learning. Project DEFY promotes resourcefulness, experimentation, and peer-to-peer learning, challenging conventional education with its "Design Education For Yourself" (DEFY) approach (Vones, K ,2022).

Image credit: Project DEFY

An Experiment: Unbox in Jammu

A recent pilot study in Jammu underscores the significance of student agency in education. This study introduced the innovative "Unbox" program to local schools, emphasising student choice, hands-on engagement, and self-directed learning.

Image Credit: UnBox, Soc Education LLP

The UNBOX Toolkit, created by SoC Education LLP, caters to children aged 3-10, promoting "Self-Directed Learning" through open-ended art exercises called "कला-कसरत (Kala-Kasrat)." This approach aligns with fundamental learning principles and aims to rekindle children's innate creativity, counteracting the typical decline in creativity with age.

The study's findings in Jammu highlight the positive impact of student agency on learning outcomes. Participation in the Unbox program resulted in improved skills application, enhanced problem-solving abilities, and overall classroom performance.

Behaviour Economics for Learning:

All these examples reflects a broader trend in the educational landscape, where there's a growing fascination with integrating behavioural economics principles in classrooms. One notable example is the use of gamification, where game elements and mechanics are incorporated into educational activities to motivate and engage students (Deterding et al., 2011). Gamified interventions leverage behavioural economics concepts like rewards, incentives, and feedback loops to encourage desired behaviours and learning outcomes. Another approach involves the use of token economies in classrooms, where students earn tokens for positive behaviours or academic achievements. This intervention draws from behavioural economics' demand function theory, assessing how changes in effort or resources (tokens, in this case) influence student engagement and learning outcomes(Kim, 2022). Additionally, interventions that incorporate the principles of "nudging" (Thaler & Sunstein, 2008) have been explored in educational settings. In education, nudges can be used to encourage students to complete assignments on time, make healthier food choices, or even prompt them to attend class regularly. However, a limitation of nudges is their short-term impact, prompting ongoing research efforts to extend their effectiveness(Chen, 2022).

Nonetheless, these interventions rooted in behavioural economics offer promising avenues for improving educational outcomes by addressing behavioural challenges and optimising decision-making processes.

As Nobel laureate Richard Thaler aptly puts it, "If you want to encourage some activity, make it easy." This principle resonates with the core tenets of behavioural economics and their application in education, where interventions aim to facilitate and streamline the learning process. By understanding how students acquire and process information, educators can design interventions that align with their cognitive capabilities and promote effective learning.

Contributions: Farheen and Khushi

Editor: Aurko


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