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By Taylor Martin • April 20, 2022

The 7 Key Elements of eSpark’s Theory of Learning

eSpark’s Theory of Learning is grounded in seven research-based elements – teaching practices or curriculum design elements – that are directly linked to student learning outcomes.

These elements are: differentiation, adaptivity, student engagement, direct instruction, practice, formative assessment with immediate feedback and student explanation of learning. Here is a look at the research and principles that greatly influence eSpark’s curriculum.

1. Differentiation Keeps Learning Accessible

When a student first logs onto eSpark, they’re welcomed with a placement quiz to find their individual learning level. Though the students are continually assessed throughout the program to adjust to their skills, this initial reading in our curriculum design sets them on a path tailored to their needs. Why do we do this?

Research shows that differentiated content leads to greater student reading growth (Reis et al., 2011). This is particularly true when resources are provided for teachers to more easily differentiate (Otaiba et al., 2011).

2. Adaptivity Allows For Growth

In order to continually adapt to each student’s needs, eSpark administers a pre and post-quiz during each Quest. And, if a student struggles to master more than 50% of their Quests within a Grade-Level Domain, they are dropped down to an easier version of the same material. When they complete the easier content, they’re moved back to their original difficulty level to try again.

This strategy keeps students working with content that is neither too difficult nor too easy for their individual level. Our adaptive pathways consistently adjust within the student’s Zone of Proximal Development (Vygotsky, 1978). In demonstration of this theory, one study found that students who receive adaptive testing paired with individualized instruction show significantly better performance than their peers who receive more generalized instruction (Huey-Min, 2017).

3. Student Engagement Increases Motivation

Rather than relying on scores and praise, eSpark's curriculum design uses interactive videos, songs, games and texts to motivate students. They’re encouraged to complete Quests simply for the fun of the activities. To ensure students are enjoying the games, we use a thumbs up/down method to collect feedback after every activity. Our team uses an 85% positive rating as a baseline. How do we know that engaging students works better than scores and praise?

Studies have shown a significant, positive correlation between intrinsic motivation and achievement in GPA and standardized test scores as well as negative relationships between extrinsic motivation and the same achievement scores (Lepper et al., 2005). Furthering this, both time on instruction and student engagement have produced a significant, positive association with achievement in math (Bodovski et al., 2007).

4. Direct Instruction Ensures Success

With eSpark’s focus on direct instruction, students are provided multiple opportunities to ensure that the skills they are learning are explicitly taught. Students need more than just practice to learn a skill, so direct instruction is front-and-center in the curriculum. Each eSpark Quest includes at least two engaging instructional videos which provide direct instruction through songs, cartoons, worked examples, and more.

Such direct instruction videos are interspersed between practice activities to ensure every skill is taught explicitly in a way that students will be able to transfer to independent practice (Fisher & Frey, 2007). Step-by-step instruction, particularly with math, and clear goal or expectation setting both increases test scores and improves the attitudes of students who struggle (Al-Makahleh, 2011).

5. Practice Leads to Mastery

For both reading and math activities, eSpark provides students with multiple opportunities to practice the skills they’re learning. The type of instruction and practice in our curriculum design depends on the subject area students work on, but both offer several different kinds of opportunities from games to quick checks to critical thinking challenges. Does practice really make perfect?

Providing both visual representations and a range of examples instills a deeper understanding of mathematics concepts and develops strong mathematical knowledge in students (Gersten et al., 2009). eSpark’s curriculum involves monitoring comprehension, asking questions, generating questions, summarization and the use of graphic organizers. Each of these strategies have proven to lead to increased learning, better transfer of learning, increased retention and overall improvements in comprehension (National Reading Panel, 2000).

6. Formative Assessments and Feedback Fuel Understanding

So, how do we know the students are learning from eSpark? Every eSpark video, activity and game features at least one check for understanding question. Students always receive feedback on their answers and if they’re wrong, they’re given feedback on how to answer similar questions in the future.

Even simple feedback, such as right or wrong, has been correlated with student learning outcomes (Faber et al., 2017). Alongside the feedback, eSpark students are permitted multiple attempts on assessments and challenges. Allowing students multiple attempts at mastering concepts is correlated to higher learning levels (Martinez J., & Martinez, 1992).

Students aren’t the only ones who receive feedback. Providing teachers with data on their students’ learning levels and suggested materials aligned to their gaps is correlated to student learning outcomes (Bergan et al., 1991). Teachers receive real-time formative assessment data, a strategy that is also linked to positive learning outcomes (Pape et al., 2012).

7. Student Explanation of Learning Aids Retention

The retention and transfer of skills is a key indicator of eSpark’s effectiveness. To ensure students retain what they learn from our videos and activities, eSpark asks them to create a video explaining what they’ve learned. This opportunity to demonstrate higher level understanding allows the student to become the teacher.

By verbally responding to a prompt, students are able to become the teachers and are much more likely to be able to transfer what they have learned (Rittle-Johnson, 2006). Even when compared to written responses, students of all ages are better able to retain what they have learned when they explain it verbally (Hoogerheide et al., 2016).

Overall, these seven research-based elements are instrumental in providing students with fun, individualized instruction focused on skill improvement.

For more information about eSpark's curriculum design, contact us below.

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Al-Makahleh, A. A. (2011). The Effect of Direct Instruction Strategy on Math Achievement of Primary 4th and 5th Grade Students with Learning Difficulties. International Education Studies, 4(4). https://doi.org/10.5539/ies.v4n4p199

Bergan, J. R., Sladeczek, I. E., Schwarz, R. D., & Smith, A. N. (1991). Effects of a Measurement and Planning System on Kindergartners’ Cognitive Development and Educational Programming. American Educational Research Journal, 28(3), 683–714. https://doi.org/10.3102/00028312028003683

Bodovski, K., & Farkas, G. (2007). Mathematics Growth in Early Elementary School: The Roles of Beginning Knowledge, Student Engagement, and Instruction. The Elementary School Journal, 108(2), 115–130. https://doi.org/10.1086/525550

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Gersten, R., Chard, D. J., Jayanthi, M., Baker, S. K., Morphy, P., & Flojo, J. (2009). Mathematics Instruction for Students With Learning Disabilities: A Meta-Analysis of Instructional Components. Review of Educational Research, 79(3), 1202–1242. https://doi.org/10.3102/0034654309334431

Hoogerheide, V., Deijkers, L., Loyens, S. M. M., Heijltjes, A., & van Gog, T. (2016). Gaining from explaining: Learning improves from explaining to fictitious others on video, not from writing to them. Contemporary Educational Psychology, 44-45, 95–106. https://doi.org/10.1016/j.cedpsych.2016.02.005

Huey-Min Wu, Bor-Chen Kuo, & Su-Chen Wang. (2017). Computerized Dynamic Adaptive Tests with Immediately Individualized Feedback for Primary School Mathematics Learning. Journal of Educational Technology & Society, 20(1), 61–72.

Lepper, M. R., Corpus, J. H., & Iyengar, S. S. (2005). Intrinsic and Extrinsic Motivational Orientations in the Classroom: Age Differences and Academic Correlates. Journal of Educational Psychology, 97(2), 184–196. https://doi.org/10.1037/0022-0663.97.2.184

Martinez J., & Martinez, N. (1992). Re-examining Repeated Testing and Teacher Effects in a Remedial Mathematics Course. British Journal of Educational Psychology, 62(3), 356–363. https://doi.org/10.1111/j.2044-8279.1992.tb01028.x

National Reading Panel. (2000). Teaching children to read: An evidence-based assessment of the scientific research litera- ture on reading and its implications for reading instruction (NIH Publication No. 00-4769). Washington DC: U.S. Depart- ment of Health and Human Services, National Institute of Child Health and Human Development.

Otaiba, S. A., Connor, C. M., Folsom, J. S., Greulich, L., Meadows, J., & Li, Z. (2011). Assessment data-informed guidance to individualize kindergarten reading instruction: Findings from a Cluster-Randomized Control Field Trial. Elementary School Journal, 111(4), 535–560.

Reis, S., McCoach, D., Little, C., Muller, L., & Kaniskan, R. (2011). The Effects of Differentiated Instruction and Enrichment Pedagogy on Reading Achievement in Five Elementary Schools. American Educational Research Journal, 48(2), 462-501. Retrieved June 13, 2021, from http://www.jstor.org/stable/27975296

Rittle-Johnson, B. (2006). Promoting Transfer: Effects of Self-Explanation and Direct Instruction. Child Development, 77(1), 1–15. https://doi.org/10.1111/j.1467-8624.2006.00852.x

Stephen J. Pape, Karen E. Irving, Douglas T. Owens, Christy K. Boscardin, Vehbi A. Sanalan, A. Louis Abrahamson, Sukru Kaya, Hye Sook Shin & David Silver (2012) Classroom connectivity in Algebra I classrooms: results of a randomized control trial, Effective Education, 4 (2), 169-189, DOI: 10.1080/19415532.2013.841059

Vygotsky, L. S. (1978). Mind In Society: Development of Higher Psychological Processes. Harvard UP.


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