Education Week 3 assignment

Running head: DIGITAL TOOL IN EDUCATION AND FORMATIVE ASSESSMENT 1

Digital Tools in Education and Formative Assessment

Brenda Rouse

St Thomas University

EDU 530 Educational Measurement

Dr. Pamela Dahlin

January 26, 2025

DIGITAL TOOLS IN EDUCATION AND FORMATIVE ASSESSMENT 2

Digital Tools in Education and Formative Assessment

Step 1: Topic Exploration

Chosen Topic: Digital Tools in Education and Formative Assessment

Research Summary:

Digital tools included in education and formative assessment are the go-to in education. The

three findings from the peer-reviewed research disclose the following:

1. Challenges in Teachers' Adoption: Borte et al. (2023) highlight that incongruence in

the realm of technology versus pedagogy prevents teachers from taking advantage of the

full potential inherent in digital tools-stimulating student-centered learning or even

formative assessment practices definition and more teacher training in data literacy.

2. Evidence of Effectiveness: According to Sortwell et al. (2024), formative assessment

practices positively influence the learning process for students in K-12 if done

appropriately. However, more research is needed, given the low certainty of evidence

concerning optimal strategies.

3. Personalized Learning: Weigand, Trgalova, and Tabach (2024) have discussed how

digital tools, especially adaptive systems, allow individualized learning experiences and

formative assessments in mathematics education. These tools provide real-time feedback

that helps students and teachers address specific learning needs.

4. Gaps in Current Research: All three note that digital formative assessment strategies'

effectiveness and long-term impact on students' engagement and outcomes remain under-

researched.

DIGITAL TOOLS IN EDUCATION AND FORMATIVE ASSESSMENT 3

5. Challenges for Teachers: Some challenges that hold back teachers are the limitations of

the technology itself, the lack of training to use these technologies, and the lack of

research on best practices for using these technologies within formative assessment.

Step 2: Narrow Focus

Narrowed Topic:

The potential of Artificial Intelligence (AI) ventures to realize an impact on enhancing

formative assessment through personalized feedback and specific challenges in teachers'

implementation of ventures.

Relevance to Assessment and Measurement:

This topic is relevant because formative assessment is a cornerstone of effective teaching

and learning. Other challenges include equity, teacher autonomy, and professional development

when integrating AI. It can lead to insightful ways to design practical AI-driven formative

assessment tools and further knowledge of the broader implications for K-12 education.

Step 3: Crafting the Guiding Question

Guiding Research Question:

How could AI-embedded formative assessment improve personal feedback and decision-

making in K-12 education, and what does that indicate for the workload and burden of teachers?

Rationale:

The guiding question cuts into what is critical and timely: technology and education must

work at a crossroads that transform AI possibilities within formative assessment. Therefore, it is

because AI provides unlimited ways of constructing productive personalized feedback that can

eventually be useful to teachers and educators in providing teaching strategies that can

accommodate needs that will be different for different learners; it promises improved results in

DIGITAL TOOLS IN EDUCATION AND FORMATIVE ASSESSMENT 4

better learning. For example, it would not be easy to get data education for those teachers by

using new technologies and weighing those tools with professional judgment. However, there is

an entire issue of equity, access, and ethical issues regarding the use of AI in many K-12 settings.

In keeping with the ongoing debate about new inventions in measurement and assessment, there

seems to be some search for possibilities in harmony with restrictions about the prospect and

usage of formative assessments via AI. For these reasons, such research allows for actual

development in ways that will help make any final equitable, vigorous AI-supported assessments

feed into teachers and eventually improve the quality of teaching and learning for a regiment of

students across all contexts. Additionally, frameworks like the Learning-with-PA Model

highlight the importance of contextual factors and digital agents in mediating learning outcomes

(Dolata et al., 2023).

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References

Børte, K., Lillejord, S., Chan, J., Lillehaug, B. W., & Greiff, S. (2023). Prerequisites for

teachers’ technology use in formative assessment practices: A systematic

review. 100568 ; Educational Research Review ; 41.

https://doi.org/10.1016/j.edurev.2023.100568

Dolata, M., Katsiuba, D., Wellnhammer, N., & Schwabe, G. (2023). Learning with Digital

Agents: An Analysis based on the Activity Theory. Journal of Management Information

Systems, 40(1), 56–95. https://doi.org/10.1080/07421222.2023.2172775

Sortwell, A., Trimble, K., Ferraz, R., Geelan, D. R., Hine, G., Ramirez-Campillo, R., Carter-

Thuiller, B., Gkintoni, E., & Xuan, Q. (2024). A Systematic Review of Meta-Analyses on

the Impact of Formative Assessment on K-12 Students’ Learning: Toward Sustainable

Quality Education. Sustainability, 16(17), NA. https://doi.org/10.3390/su16177826

Weigand, H.-G., Trgalova, J., & Tabach, M. (2024). Mathematics teaching, learning, and

assessment in the digital age. ZDM, 56. https://doi.org/10.1007/s11858-024-01612-9