Differentiated Education Using Technology in Junior and High School Classrooms

Definition

This entry presents the findings of a bibliographic review in Differentiated Instruction (DI), emphasizing its importance in classrooms with diverse student abilities. DI encourages teachers to adjust their instructional methods based on students’ learning profiles and needs. It has been identified as a crucial strategy for fostering inclusion and equal opportunities in education. Overall, the document underscores the importance of DI in fostering personalized learning and equal opportunities, especially in diverse classrooms. It also highlights ongoing challenges, such as teacher preparation, time constraints, and the need for the effective use of technology and data.

1. Introduction

In contemporary Greek society, it is an undeniable right of everyone to have access—both physical and digital—to all areas and services. The current Greek system must support the education of today’s learners and future citizens by ensuring they use accessibility tools effectively, while also cultivating empathy to facilitate easier access for all (inclusive education). The role of the modern teacher or philosopher must evolve to align with this shift. Educators require resources that motivate and connect with their students. The newly developed curricula appear to offer a foundational tool, enabling structured material and the application of differentiated teaching methods. This entry follows an integrative literature review approach. Articles were selected from databases, such as Google Scholar, Web of Science, and ERIC, using predefined keywords. Selection criteria included peer-reviewed status, relevance to DI, and publication within the last ten years.

For DI to be implemented, the necessary technological support is required, allowing secondary education teachers to apply it both in the production of material and in teaching. Additionally, students themselves must be able to use, apply, and create with these tools. DI is a pedagogical approach designed to respond to student diversity by adapting the content, process, product, and learning environment [1].

DI is more than just an innovative teaching approach; it is a pedagogical theory rooted in the principles of inclusion and equity. Kakana [2] described DI as a flexible framework that enables teachers to adapt instruction to students’ diverse needs, ensuring that “one size does not fit all” [2]. DI promotes equal educational opportunities, fostering student success without discrimination. Tomlinson [3] emphasized that DI involves systematic lesson planning to address students’ varying readiness levels, allowing them to achieve their full potential. It is a proactive approach that aligns with social justice values.

DI emphasizes flexible teaching methods to address students’ varying levels of readiness, interests, and learning profiles. For example, a teacher may use tiered assignments to accommodate different skill levels within the same classroom. The purpose of this entry is to analyze how DI has been conceptualized and implemented in various educational settings [4].

2. Conceptualizing Differentiated Instruction

The literature presents multiple interpretations of differentiation, often overlapping with the concept of personalized learning. While both approaches aim to tailor education to individual needs, DI primarily focuses on group instruction using flexible strategies, whereas personalized learning frequently involves student autonomy and self-directed learning [5,6]. Differentiation serves as an umbrella term that encompasses the concepts of differentiated instruction, differentiated learning, differentiated education, and personalized learning [5]. Although these terms are sometimes used interchangeably, they refer to distinct pedagogical approaches and levels of educational design.

DI refers specifically to the teacher’s intentions and actions to adapt the content, process, product, and learning environment based on students’ readiness levels, interests, and learning profiles within a classroom setting [7,8]. In contrast, differentiated learning emphasizes the students’ experience—how learners engage with and process information differently according to their unique characteristics [5]. Personalized learning is oriented toward tailoring instruction to the unique characteristics, goals, and preferences of each student, often utilizing technology to support autonomy, self-regulation, and intrinsic motivation [5,6].

At a broader level, differentiated education refers to systemic approaches that adapt the educational structure itself—such as through diverse school types or curricula—to better align with students’ varying needs, interests, and abilities [8]. These systemic approaches often incorporate instructional models such as Universal Design for Learning (UDL), which seeks to design inclusive and flexible learning environments from the outset, accommodating all learners regardless of ability or background [9,10,11]. By delineating these terms, a more structured and comprehensive framework emerges, illustrating how differentiation operates across instructional, experiential, and systemic dimensions of education.

DI has also been associated with Universal Design for Learning (UDL), a framework that provides multiple means of engagement, representation, and action/expression to support all learners. Understanding the relationship between DI and UDL is crucial, as the two approaches complement each other in inclusive education.

According to Baroni and Folci [12], DI and UDL complement each other in educational practice by fostering inclusive and effective teaching strategies. While DI focuses on adapting instruction to meet the diverse needs of students through flexible grouping, content modification, and differentiated assessments, UDL provides a proactive framework that ensures accessibility from the outset by offering multiple means of engagement, representation, and expression. In practice, UDL establishes a foundation that minimizes barriers to learning, while DI further refines instructional strategies to tailor learning experiences to individual student needs. By combining UDL’s broad accessibility principles with DI’s targeted responsiveness, educators can create classrooms that are both universally accessible and individually supportive, fostering engagement, equity, and meaningful learning for all students.

Kamran et al. [13] examined the effects of differentiated teaching compared to traditional methods in physics education. Their experimental study at Aitchison College involved random sampling with a group of 70 students. Data collection included pre-tests and post-tests to measure academic performance differences between the traditional and DI groups. Initial assessments showed that most students performed well in the lower levels of Bloom’s Taxonomy (understanding and application) but struggled with the higher levels (analysis, synthesis, and evaluation). After implementing DI, students in the experimental group significantly improved in all levels of Bloom’s Taxonomy, while those in the control group showed no change at higher levels. The research concluded that DI led to better student performance, particularly in critical thinking skills, making it a more effective teaching method than traditional approaches. Kamran et al. recommended the adoption of DI techniques for teaching physics to enhance student learning outcomes.

Ismajli and Imami-Morina [14] explored the influence of DI strategies in primary education by assessing its implementation based on the content, process, and learning products. Their study involved 200 students, 30 parents, and 30 teachers from both public and private schools, using questionnaires and interviews for data collection. The research found that students engaged more actively when their learning preferences were met through DI strategies, such as group work and active learning. However, the study also revealed challenges for teachers, who often emphasized learning products over the content and process due to a lack of proper training and support. In addition, large class sizes in both public and private schools hindered DI’s effective implementation. Parents, on the other hand, supported the use of DI in classrooms, stressing the need for cooperation between teachers and parents to facilitate personalized learning [14].

Meanwhile, accessibility refers to creating inclusive environments—both physical and digital—that are accessible to everyone, including people with disabilities. This concept extends to all products and systems, with terms like “universal design” or “design for all” used to describe such inclusive practices. Koutsampasis [15] noted that while “universal design” originated in the U.S., Europe often uses the term “design for all”. Accessibility benefits not only individuals with disabilities but also those with temporary impairments or limited physical abilities. Guidelines promoting accessible information, including Open Educational Resources (OERs), aim to make learning materials available to a broader audience. According to the World Health Organization (2023), about 15% of the global population lives with disabilities, emphasizing the need for accessible information [15,16].

Nusser and Gehrer [17] investigated whether students with special educational needs benefit from DI in German language classes compared to their peers with moderate or high academic performance. The study found that DI should not be seen as a compensatory tool for students with “deficits” but rather as an effective teaching strategy for all students, including those performing at or above grade level [18]. However, technological infrastructure, such as computers in classrooms, is necessary to implement DI principles and universal design, but many schools lack these resources [11].

While differentiated education, differentiated learning, and differentiated instruction share common elements, they have distinct meanings. Differentiated education refers to systemic adaptations, differentiated learning emphasizes student agency, and differentiated instruction focuses on teacher-driven adaptations.

3. The Role of the Teacher in Differentiated Instruction

3.1. Teachers’ Attitudes Towards ICT and Innovation in Teaching

Research on the use of digital systems in teaching and learning practices, both internationally and nationally, is extensive and primarily focuses on primary education teachers, with less emphasis on secondary education teachers. Research on the use of technologies by philologists has been scarce in Italy [19]. Secondary education teachers have a positive attitude towards the use of computers, but this is not definitive. However, it seems that they are not yet ready to embrace this innovation.

A teacher considers students’ readiness, learning profiles, interests, socioeconomic backgrounds, and self-image to tailor the content, process, outcomes, learning environment, or assessment. This approach addresses diverse learning needs, offers varied learning opportunities, and supports students in acquiring knowledge and skills within a safe, engaging, and comfortable classroom setting.

3.2. Research on the Implementation of Differentiated Instruction

A study by Gibbs and McKay, performed during 2021, examined how secondary school teachers in a large public middle school in regional Queensland implemented DI in their classrooms. DI is described as the way teachers address individual student needs in their daily practice by monitoring progress, identifying specific learning requirements, and adapting their teaching accordingly. The study also explored differentiation at a systemic level, highlighting how different types of schools are structured to accommodate students with varying abilities and how differentiation extends to distinctions between academic and vocational programs [18].

The findings indicated that teachers, school administrators, and educational institutions interpret differentiation in diverse ways, with particular focus on the role of mixed-ability classrooms. The study also emphasized the importance of recognizing the unique characteristics each student brings to the classroom, such as their interests and skills. It highlighted how teachers can adapt their instructional strategies to foster learning by responding to these attributes, ensuring that all students are supported in their academic development [18].

Given the increasing diversity among students, teachers are required to address various learning needs through DI. A study conducted in Germany by Pozas et al. [6] examined the beliefs of teachers who teach the German language as a mother tongue and those who teach mathematics. Since empirical research has provided mixed evidence on teachers’ use of DI techniques, the researchers used data from the National Educational Panel Study (NEPS) in Germany to explore the impact of teachers’ constructivist beliefs on the implementation of DI.

3.3. Teacher Beliefs, Mindsets, and Misconceptions

The study conducted in Germany by Pozas et al. [6], confirmed that teachers occasionally apply DI. However, teachers with constructivist beliefs were found to implement such techniques more frequently. Despite this, the frequency of DI varied, with older and more experienced teachers tending to use these strategies less often than their younger or less experienced counterparts. This finding suggests that teaching experience and age may influence how often teachers incorporate differentiated instructional methods in their classrooms.

Moreover, the study revealed that the overall frequency of DI was lower than the levels recommended for effectively addressing the diverse learning needs and abilities of students. In other words, teachers were not applying these strategies as often as experts suggest is necessary to manage classroom heterogeneity successfully. As a result, this gap may limit the ability to provide equitable and tailored learning experiences for all students. Nevertheless, in practice, some techniques, such as tiered tasks and heterogeneous groupings, were observed in classroom settings [6].

The suitability of teachers’ beliefs plays a crucial role in student learning [17]. According to Nusser and Gehrer, the effectiveness of DI depends on a teacher’s ability to accurately assess students’ abilities. However, research has identified discrepancies between teachers’ perceptions of their students.

Teachers often tend to overestimate the effectiveness of their instructional methods, while students may perceive these methods differently. Kunter and Baumert argue that both perspectives—teachers’ and students’—are important when evaluating teaching quality. However, they also conclude that teachers’ reports may be more reliable when a study aims “to distinguish different teaching approaches (e.g., to examine the choice and implementation of tasks separately or to investigate the characteristics of tasks defined in the classroom in more detail)” [17].

Sharp et al. identified that a shift in mindset is necessary for some teachers, specifically in moving away from misconceptions that hinder the effective use of DI. Their study revealed a widespread belief that DI simply involves adjusting the curriculum to accommodate students with additional needs, a notion that aligns with findings from Nusser and Gehrer [17].

3.4. Differentiation for Gifted and High-Achieving Students

Kokkinos and Gakis [20] explored the practices and perspectives of future educators on implementing DI for high-achieving and gifted students. DI aims to support the full spectrum of student abilities, including those who excel academically. Among the strategies they highlighted were tiered assignments, such as the R.A.F.T. (Role, Audience, Format, Topic) framework, which enhances student engagement through varied learning tasks. Another key approach is “enrichment”, which involves independent projects, in-depth explorations, activities that develop higher-order thinking skills, and the creation of authentic learning experiences.

Authentic learning is an instructional approach that connects learning activities to real-world contexts, fostering the development of practical, transferable knowledge. Grounded in situated cognition theory, it has gained recognition as an effective way to help students apply their learning in meaningful ways. Technology, particularly web-based tools and mobile devices, plays a crucial role in facilitating authentic learning, both in blended and online learning environments. By serving as cognitive tools and content delivery platforms, these technologies enhance the quality of learning experiences, making authentic learning an increasingly valuable approach as educational institutions integrate digital resources into their curricula.

3.5. Challenges in Implementing Differentiated Instruction

According to Roberts and Inman [21], teachers face significant challenges in implementing DI due to constraints like time, resources, preparation, and standards. Creating learning experiences tailored to students’ individual needs takes more time than preparing a single lesson plan. Pre-assessments can help identify students’ prior knowledge, saving instructional time.

Teachers also need time to gather resources that meet varying student abilities, such as materials with different reading levels. A lack of adequate training on DI is another issue, as many teachers do not receive enough guidance, particularly for teaching advanced students. Observing experienced educators and engaging in discussions about differentiation could improve its implementation.

Another issue is the lack of adequate training and information on how to implement DI effectively. Teachers often do not receive enough guidance during their university education, especially when it comes to teaching advanced students. Furthermore, many teachers have not experienced DI themselves. Observing this method in practice, engaging with experienced teachers, and discussing the differentiation process would be beneficial for improving its application.

Classroom management is a concern, with some teachers associating DI with disorder. There is also a misconception that advanced students do not need additional support, though they require challenges through more complex materials and faster pacing. Roberts and Inman [21] continue to highlight that these misconceptions hinder the effective application of DI in classrooms.

The current educational system often focuses on uniform curriculum progress, applying differentiation mainly for struggling students. However, differentiation is equally important for advanced students, as it supports continuous progress by aligning learning with students’ interests, strengths, and readiness, keeping them engaged in the process. According to Roberts and Inman [21], ensuring that all students, regardless of their abilities, are challenged appropriately is crucial for maintaining motivation and fostering growth.

Additionally, differentiation allows for the more productive use of classroom time, as each student can advance at their own pace. This approach helps to reduce problematic behaviors and prevents struggling students from becoming discouraged. Students also tend to learn faster when their learning experiences are aligned with their existing knowledge and experiences. According to Sousa and Tomlinson the classroom environment can have a direct effect on a student’s IQ, with stimulating and challenging settings fostering greater intellectual development [3].

Finally, differentiation ensures fairness and equity. It is not fair to expect all students to complete the same tasks at the same time. True fairness lies in giving students the opportunity to engage in learning experiences that allow them to progress continuously, based on their individual needs. While the need for differentiation stems from students, the decision not to differentiate often reflects the limitations of the teacher.

3.6. Differentiated Instruction in the Teaching of Ancient Greek

The study of ancient Greek is crucial as it underpins Western literature, philosophy, and sciences, while also enhancing students’ linguistic and analytical skills. DI allows for a more tailored approach to teaching ancient Greek, addressing diverse student needs through adaptable methods. For instance, advanced students might engage with complex philosophical texts, while beginners focus on basic vocabulary and sentence structures. The integration of ICT tools further supports DI by offering interactive learning experiences, such as language-learning apps for beginners and advanced digital resources for in-depth analysis. While many philologists recognize the need to move beyond traditional teaching methods, opinions vary on the role of ICTs in improving instruction. Nevertheless, DI remains essential in ensuring that all students, regardless of proficiency level, stay engaged and challenged, fostering both motivation and continuous progress in learning ancient Greek [19].

Philologists believe that DI is initially required in language teaching, then in literature, in ancient Greek from the original and then from translation, while placing history at the bottom. They argue that language teaching, due to the nature of the subject as purely linguistic and its communicative orientation, is particularly suitable for DI. Another reason for applying DI is the possibility of selecting/gradating questions, exercises, and assignments given to students. Lastly, they argue that DI is necessary due to the need to consider the needs and interests of students who are likely to exhibit significant differences in their cognitive and/or linguistic levels in the contemporary multicultural classroom. The philologists’ view on literature is that, since this subject aims at aesthetic cultivation, enhancing communication skills, and the emotional development of students, it requires differentiation because the curriculum is flexible regarding teaching hours and methods, and it allows the use of different teaching materials and methods. However, philologists highlight that, due to the large volume of text that students need to cover, the possibility of differentiation is somewhat limited.

The integration of ICTs in the study of ancient Greek from the original, especially in literature, is a topic that would benefit from further study. The view of philologists that DI is essential for the teaching of ancient Greek, especially in language teaching and literature, is well-founded given the diverse cognitive and linguistic levels of students. The application of ICTs could potentially enhance these differentiated practices, though more research would be valuable to explore the practical implementation and effectiveness of such approaches in ancient Greek education [22].

3.7. Teacher Readiness and Inclusive Education

According to Gheyssens et al. [5], teachers often face considerable pressure and feel insufficiently equipped to foster inclusive classroom environments. To better address student diversity and promote inclusivity, DI has been promoted to meet individual learning needs and optimize learning opportunities. While DI was initially introduced to support gifted students, it has since evolved into a broader pedagogical approach aimed at serving all learners in mixed-ability classrooms. The authors emphasize the importance of implementing DI in these contexts and explore the distinctions between teachers who simply adopt DI strategies and those who apply them with intentionality and depth.

Their analysis centers on the DI-Quest model, which includes four foundational components as follows: developing a growth-oriented mindset, acting with an ethical compass, the ability to group students flexibly, and the principle of “output equals input”, where student outcomes serve as feedback for both students and teachers. These components are key predictors of a fifth, pivotal element—adapting instruction according to students’ readiness levels, interests, and learning profiles. This final element captures the essence of DI, reflecting its core goal—tailoring instruction to address three central aspects of student diversity. Gheyssens et al. argue that teachers who strongly believe in the value of adjusting instruction based on classroom learning responses are more likely to apply adaptive teaching practices effectively, aligning with the central tenets of DI [17].

4. The Role of the Student in Differentiated Instruction

The modern student population, characterized by varying abilities, motivations, knowledge, experiences, and needs, makes it essential to integrate students with and without specific learning difficulties, as well as to apply DI in general education classrooms. According to Sourtzi et al. [23], DI is designed by the teacher to achieve effective learning for each student, particularly focusing on those who face learning and developmental challenges. However, this does not mean fully individualized education. As emphasized by the same authors, learning pathways are differentiated through collaborative processes, with students being engaged in projects and situations requiring problem-solving and the solution of dilemmas. These situations generate needs that shape and guide the differentiated interventions of the teacher, or rather, the educators who are called upon to collaborate for the benefit of the students. In this context, differentiation in teaching creates a classroom environment that does not threaten students’ identity, safety, or mental availability. It ensures that learning is meaningful, motivating, challenging, and positioned within their zone of proximal development [23]. In other words, it pertains to what the student can accomplish through accessible learning with instructional support. As cited in Sourtzi et al. [23], Panteliadou stresses that “what a student learns, how they learn, and how they demonstrate what they have learned must match their level of readiness, interests, and learning preferences”. This highlights the following two central pillars in the process of DI: the student and the curriculum [23].

DI places students at the center of the teaching process, where they can access learning at their own pace. It respects each student, utilizing their individual characteristics and acknowledging their different abilities [18]. The strategies developed create a positive social, emotional, and physical classroom that enhances student learning and increases student motivation.

Gibbs and McKay [18] note that it was challenging to apply differentiated scenarios to high-performing students (e.g., swimming/lifesaving), as their assessment was based on formal award criteria rather than their readiness and interests. Teachers expressed concerns about safety, the time-consuming process of individualized assessments, and the limitations of “space/numbers, time, and student readiness”, making it a challenge to ensure each student could achieve their learning goals [18].

Coubergs et al. [5] argue that when dealing with diverse classrooms, teachers need to design their instruction with students’ individual learning profiles in mind [17]. They also emphasize the need for further research on how DI influences the development of specific skills in particular student groups. Schwab [24] adds that as classrooms become increasingly diverse, implementing differentiated teaching methods becomes essential, especially within co-education settings.

Research conducted across four primary schools, which examined the use of data for student grouping [25], found that mixed-ability grouping, where high-performing students were included, had a positive impact on the performance of lower-achieving students. This approach also helped enhance students’ critical thinking skills, especially in mathematics, by grouping students strategically so they could benefit from each other’s thought processes.

5. Data-Driven Decision Making (DDDM) and Data Collection

The idea of using data to guide educational and school improvement is not new [26]. The terminology used is either Data-Driven Decision Making (DDDM) and Data-Based Decision Making (DBDM), with both terms referring to the exact same procedure. With DBDM, it is expected that data are collected and used more systematically by schools [27]. Data need to be identified, collected, analyzed, and interpreted before action is taken [25]. This way, teachers can set realistic performance goals for students. The DBDM process is cyclical and involves four steps. Initially, (first step) the teacher collects data on their students, and then (second step), clearly formulated goals are set. In the third step, they define their instructional strategy, matching the students’ needs based on the first and second steps. Finally (fourth step), the teachers implement their planned teaching strategies in the classroom. After this step, the cycle starts again by analyzing the impact of the strategies applied. In DBDM, the four elements of the cycle are interconnected [28].

Park and Datnow [26] highlight that the factors shaping decision making for the implementation of DDDM remain insufficiently studied. They argue that we know little about the types of data teachers use, how decisions are made, and how teaching is influenced. They note that while differentiation is considered a decision made by the teacher, in reality, decisions are often made at the school or district level, guiding teachers. They believe that data use is a crucial piece of this puzzle. DDDM is not just an individual activity but also a social and organizational process shaped by decisions, policies, and structures implemented at multiple levels. The use of data, especially “accountability data”, has led to both promising and problematic teaching practices. On the one hand, the use of data has been associated with improved student achievements or school practices, creating a powerful tool for teachers to reflect on their students’ capabilities and their teaching practices. On the other hand, they argue that data may reinforce inequalities among students and perpetuate narrow assumptions about students’ abilities.

Booher-Jennings [29] recorded that in high-stakes, resource-limited environments, the use of data has led to negative practices, such as focusing on “bubble” students, who are seen as having the greatest potential for improvement. However, this focus on students who are close to meeting the required thresholds for success often overlooks those who are either struggling or excelling. Additionally, data do not always lead to new or deeper interpretations of students’ abilities, as the emphasis on certain groups can limit a more comprehensive understanding of diverse student needs.

The term “bubble students” refers to those who are on the cusp of reaching a higher achievement level or threshold, typically just below the cut-off for advancement or success, but still above the minimum required to avoid failure. These students are often the focus of “intensive promotion” efforts, as educators or educational systems concentrate on improving their performance to achieve better outcomes, such as higher test scores or improved school success rates. In many educational systems, bubble students are seen as those with the greatest potential for success with the right support and intervention. However, this focus can have unintended consequences, such as neglecting students who are either struggling significantly or performing at higher levels, as they are not immediately seen as “close” to the success or failure thresholds. Therefore, the continued focus on bubble students can limit personalized learning and lead to superficial applications of DI as the system becomes overly focused on this group at the expense of others with different needs [30].

Additionally, Goertz et al. [31], found that teachers used assessment results to validate their beliefs about students’ strengths and weaknesses, setting their own performance thresholds for students and categorizing some as “capable” or “at risk”. These thresholds varied depending on the context, the student, and the assessment, highlighting the central role of the teacher in the use of data.

Assessment data play a significant role in DDDM, particularly for grouping students. For instance, Hoover and Abrams [32] note that “Elementary teachers (97%) were more likely to use data to make changes to student groups than middle school (81%) or high school (66%) teachers”. However, there is no evidence on data-driven decision making regarding group stability. In a qualitative study by Datnow et al. [33], high school teachers used weekly assessments to group students in math and English classes.

In the study by Datnow et al. [33], semi-structured observation protocols were utilized to document the types of data discussed, as well as how the data were analyzed in relation to student performance and background. Data collection protocols at a school and group level, analyses of common assessments, benchmarks, and formative assessments by teachers were gathered. During DDDM implementation, teachers used websites supported by one-to-one device availability, such as iPads, Chromebooks, or laptops.

In some urban districts, policies were implemented to regulate how long students should use specific educational programs and how often they should be assessed. These policies were designed to maintain consistency and structure across schools. In contrast, in rural or semi-urban districts, teachers were given more autonomy to decide how frequently and for how long students engaged with these programs. Teachers used online tools to assign language and math activities that allowed students to work at their own pace. Moreover, these programs were designed to support teachers in creating targeted lessons for small groups, thus addressing the individual learning needs of students more effectively.

Karst et al. [34] argue that while teachers have access to various data on students’ learning needs, such as past scores, they often do not analyze these data in depth. This may be due to factors like limited time and insufficient skills in interpreting the data effectively [34]. Even when teachers do adapt their teaching based on these data, the adjustments may not always be effective, particularly for high-achieving students. For instance, Prast, Weijer-Bergsma, Kroesbergen, and Van Luit, as cited in Karst et al. [34], found that teachers reported using differentiated strategies for high-performing students less frequently. They suggest that the main challenge lies in creating a clear and consistent connection between assessment data and DI.

Faber et al. [28] note that, according to Mandinach, governments expect data-driven practices in education to improve student performance. As a result, systematic assessment processes are encouraged by governments, and the importance of using objective and empirical data is emphasized for school improvement [28]. Schools systematically collect and organize data, such as student performance data, classroom observation data, or parent survey data, to represent various aspects of school operation [35]. Although, in theory, schools are expected to systematically collect and organize data—such as student performance records, classroom observations, and parent feedback—this is not the reality on a global scale. In many countries, including Greece, the systematic collection and use of data to inform educational decision making remains limited and fragmented [36]. Research shows that educators are often not adequately trained in data use, and the culture of data-driven practices has not been fully established in many educational systems [37,38]. In the Greek context, efforts have been made to introduce Data-Driven Decision Making (DDDM), yet the lack of a comprehensive institutional framework and the absence of organized tools continue to present major challenges [39]. Therefore, the concept of systematic data use should be approached critically and contextualized within the educational realities of each country.

Faber et al. [28] use Ikemoto and Marsh’s [40] definition of DBDM: “Teachers, principals, and administrators systematically collect and analyze data to guide a range of decisions that will help improve student and school success”. However, they note that research results on the actual impact of DBDM on student performance vary [41]. Data-Based Decision Making (DBDM) refers to the systematic process through which educators collect, analyze, and use various forms of data—such as student assessments, behavioral records, attendance, and classroom observations—to inform and guide instructional decisions, school improvement efforts, and policymaking [38]. The goal of DBDM is to enhance educational outcomes by ensuring that teaching practices and administrative strategies are evidence-based and tailored to students’ needs. The term DBDM is often used interchangeably with Data-Driven Decision Making (DDDM). However, some scholars argue that DBDM is more specific to educational settings, placing greater emphasis on the interpretation of multiple data sources within the school context rather than merely responding to quantitative outcomes [42]. DBDM promotes a reflective and informed decision-making culture that supports differentiation, inclusion, and equity in education [37]. For DBDM to be effectively implemented, educators must be data-literate—that is, capable of understanding, interpreting, and applying data insights in ways that are pedagogically meaningful.

Some researchers found no impact [43], others found significant results for specific student groups [44], and others observed overall significant improvements in student performance [27,45,46,47]. Although each of these studies focused on DBDM practices, the interventions varied [41]. In Van Kuijk et al.’s study [47], teachers learned new instructional skills and knowledge about teaching reading comprehension in addition to DBDM, making it difficult to interpret DBDM’s contribution.

In summary, Faber et al. [28] highlight that we still know little about how DBDM can best be used to improve student outcomes. Interventions and their results vary, and since DBDM is often a component of an intervention package, it is unclear which aspect of the intervention caused the observed effects on student performance. DBDM seems like a promising approach for school development and instructional improvement (Carlson et al., 2011 [45]; Konstantopoulos et al., 2013 [46]; Mandinach, 2012 [26]; and Van Kuijk et al., 2016 [47]), but we lack knowledge about how DBDM affects the process.

Faber et al.’s study aims to investigate the relationship between DDDM and student performance within a DBDM framework [28]. The results of DBDM interventions on student performance have been examined in several research projects (Carlson et al., 2011 [45]; Cordray et al., 2012 [43]; Konstantopoulos et al., 2013 [46]; May and Robinson, 2007 [44]; Van Geel et al., 2016 [27]; and Van Kuijk et al., 2016 [47]); however, our understanding of how DBDM impacts student performance is still very limited. The purpose of the present study was to explore the relationship between DDDM and student performance within a DBDM framework [28].

Järvinen et al. [48] examined the effect of a digital learning platform on DI and student outcomes. Students’ scores improved, suggesting that differentiated strategies and immediate feedback helped lower-achieving students the most. In addition, the platform relieved students from stress and performance anxiety, as Ashcraft [49] observed.

6. Discussion and Implications

The literature widely acknowledges DI as an effective instructional approach for addressing diverse student needs across educational settings [7,8]. Its integration with Personalized Learning and UDL highlights the need for a coherent framework that combines these methodologies to enhance student engagement and learning outcomes [9,10]. When applied effectively, DI allows for tailored instruction based on students’ readiness levels, interests, and learning profiles [50].

Data-Driven Decision Making (DDDM), sometimes referred to as Data-Based Decision Making (DBDM) in education, plays a pivotal role in the success of DI [38]. It involves continuous assessment and analysis of student performance data to guide instructional planning and inform pedagogical decisions. DDDM supports the adaptability of teaching strategies by providing educators with evidence to adjust their instruction in real time [28].

The success of DI largely depends on the interplay between the following three key stakeholders: the teacher, the student, and the DDDM process. Teachers are responsible for designing and delivering instructions that meet students’ varying needs, while students must actively engage with and respond to these differentiated opportunities. DDDM serves as the connecting mechanism, ensuring that instructional decisions are based on actual student data, thereby enhancing the responsiveness and continuity of teaching [51].

Despite its potential, the implementation of DI presents significant challenges. One major limitation is the increased workload for teachers, who must plan, manage, and assess diverse activities for students at different levels of readiness [6]. This can lead to teacher fatigue and difficulties in maintaining instructional balance. Moreover, the effectiveness of DI can be hindered by insufficient professional development, lack of institutional support, and difficulties aligning assessment data with the appropriate instructional adjustments [52].

Future research should explore effective strategies for implementing DI sustainably, examine the role of DDDM in optimizing differentiated approaches, and identify ways to support teachers in managing the practical demands of DI without compromising quality.

7. Conclusions

This entry emphasizes the importance of a well-defined understanding of DI, its relationship with personalization and UDL, and the role of data in instruction. Educators should consider these factors when designing their teaching strategies to ensure inclusivity and effectiveness.

DI is emerging as an important pedagogical approach in today’s increasingly diverse classrooms. By responding to students’ diverse learning needs through adaptable teaching strategies, DI promotes inclusivity and equity in education [3,11]. As this entry highlights, the benefits of DI extend to all students, not just those with learning difficulties, and they offer increased opportunities for engagement and success at different academic levels [21].

However, the practical application of DI still faces significant challenges. Time constraints, limited resources, and inadequate teacher training continue to hinder the effective implementation of DI strategies. In addition, the integration of technology, while promising, remains underutilized, particularly in secondary education. To fully realize the potential of DI, education systems need to provide more robust support structures, including professional development for teachers, access to technological tools, and policies that facilitate flexible learning environments.

Moreover, DI’s emphasis on personalized learning is consistent with broader educational goals of fostering critical thinking, creativity, and lifelong learning. Continued refinement of DI techniques, coupled with effective data-driven decision making, will be critical in ensuring that all students, regardless of ability or background, are provided with equitable learning opportunities.

Finally, it seems that technology is a crucial factor and can play an important role in the application of DI, especially in high schools, where children are very accustomed to technology. The issue remains the adaptation of both the teachers and the curriculum to an extent whereby the teachers will be able to act with more freedom.

This entry highlights the critical role of teacher adaptability, student agency, and data-informed instructional strategies in effective DI. Future research should focus on empirical studies that examine the impact of these factors in diverse educational settings.