The Impact of Online Video-Based Teacher Professional Development on Instructional Practices and Student Achievement in Biology

Abstract

This study aimed to examine the effects of online, video-based teacher professional development on changes in classroom instruction and student achievement in biology. The professional development program included organizing lessons based on prepared materials aligned with national curriculum outcomes, asynchronous participation in an online forum for (self-)analysis of lesson videos using the Teaching Observation Form (TOF), and synchronous participation in online communities of practice. Teachers and their eighth-grade students participated in this quasi-experimental study, which involved control and experimental student groups and pre- and post-tests of knowledge. The results indicate that students in the experimental group achieved statistically significantly higher post-test scores than those in the control group (d = 0.26), with the largest differences observed in tasks requiring higher-order cognitive skills. The findings suggest that even a relatively short professional development intervention—including continuous online support for teachers—can lead to improvements in student learning outcomes.

1. Introduction

Professional development comprises both planned activities and natural learning experiences (Day & Leitch, 2007), each of which may positively influence teachers’ knowledge, skills, attitudes, beliefs, and teaching practices (Darling-Hammond et al., 2017; Desimone, 2009; Fraser et al., 2007) and thus contribute to their professionalization (Evans, 2014). Effective professional development can also improve student learning outcomes (Guskey, 2002; Wei et al., 2009). However, despite significant investments of time (OECD, 2019) and financial resources (World Bank, 2018), many interventions fail to achieve lasting or significant improvements in education (Jacob & McGovern, 2015). Meta-analytical studies by Fryer (2017) and Sims et al. (2025) have reported relatively small average effects of professional development programs. Nevertheless, it would be inappropriate to conclude that professional development does not contribute to changes in teaching. Rather, existing programs lack sufficient effectiveness and must be fundamentally revised to foster deep teacher learning that can lead to changes in practice.

In addition to supporting teacher learning, professional development is a crucial factor in improving the education system (Opfer, 2016). This is especially relevant for education systems that, in their efforts to move from good to great, place strong emphasis on the professionalization of teachers. As noted by Barber et al. (2010, p. 40), “the path to school system improvement now relies on the fidelity of educators’ practice in their teaching and learning routines,” which can be achieved by improving the availability and quality of professional development. According to the European Commission’s (2025) assessment, Croatia lacks “qualified subject teachers in secondary education, especially in STEM subjects” (p. 12), and one proposed measure to address this problem is the improvement and further development of professional development models.

System efficiency is often evaluated by using external instruments such as the international PISA study, which measures the reading, mathematics, and scientific literacy of fifteen-year-old students. Of relevance to this paper is scientific literacy, which, according to the OECD Programme for International Student Assessment (PISA) definition, refers to the “ability to engage with science-related issues and with the ideas of science as a reflective citizen. A scientifically literate person is willing to engage in reasoned discourse about science and technology, which requires the competencies to explain phenomena scientifically…, evaluate and design scientific enquiry…, and interpret data and evidence scientifically” (OECD, 2017, p. 22). The National Academies of Sciences, Engineering, and Medicine (2016) emphasize that scientific literacy is important because it contributes to individuals’ personal development as well as to the economic, democratic, and cultural development of contemporary society.

To support the development of Croatian society, the Croatian Parliament (2021) adopted a national strategy that identifies educated and employed citizens as a strategic goal. One criterion for assessing progress toward this goal is students’ performance in PISA, with the aim of reaching the OECD average by 2030. Nevertheless, the 2022 PISA results indicate that only 5% of Croatian students attain levels 5 and 6, which represent the highest levels of scientific literacy, while the majority (72%) perform at intermediate levels (2–4), and 22% remain below the basic level (Markočić Dekanić et al., 2023). Moreover, since 2006, when Croatia first participated in PISA, Croatian students have shown a continuous decline in scientific literacy performance (Figure 1). These findings underscore the need for changes in science education to strengthen Croatian students’ scientific literacy. The curricular reform introduced in Croatia in 2019 aims to address this need by promoting scientific literacy through subjects such as Nature and Biology. However, reform alone cannot be effective without adequate support for teachers through high-quality and accessible professional development (Schleicher, 2016).

Against this background, the aim of this study is to empirically examine the effects of a professional development program on the quality of biology instruction and student achievement within a quasi-experimental design. Accordingly, the study addressed the following research questions:

(i)

Do professional development activities lead to measurable changes in biology instruction?

(ii)

Do students in the experimental group attain higher achievement in biology than students in the control group?

(iii)

Do educational outcomes differ between the experimental and control groups depending on the cognitive level of the tasks? In line with the stated research questions, the following hypotheses were proposed:

H1. 

Participation in the professional development program will be associated with measurable changes in biology instruction, as shown by assessor ratings using the TOF across recorded lessons.

H2. 

Students taught by teachers who participated in the professional development program will achieve statistically significantly higher scores in biology than students in the control group, when prior knowledge is considered.

H3. 

The effect of participation in the professional development program on student achievement will differ statistically significantly across the cognitive levels of the assessment tasks.

2. Theoretical Background

Teacher professional development is considered an important prerequisite for improving teacher learning, enhancing teaching quality and raising student achievement (Desimone, 2011). Despite ample evidence of its potential benefits, research findings are not always consistent, and a scientific consensus on effective approaches to professional development has yet to be reached (Desimone, 2023).

2.1. Major Theoretical Models of Teacher Professional Development

Desimone (2009) identifies the following stages of professional development: (1) teachers participate in professional development that is content-focused, coherent, collaborative, provides opportunities for active learning, and is of sufficient duration; (2) this professional development enhances teachers’ knowledge and skills and shapes their beliefs; (3) teachers implement what they have learned in their instructional practice; and (4) this ultimately leads to improved student learning outcomes. According to Guskey (2002), the process begins with professional development, which should result in changes in teaching and, in turn, lead to improved student learning outcomes. As a result of these changes, teachers’ beliefs and attitudes are subsequently altered. In other words, teachers’ attitudes shift only when they see that something genuinely works in practice. Clarke and Hollingsworth (2002) argue that linear models of professional development do not adequately capture the complexity of the processes that occur in practice. They therefore proposed a model comprising four interrelated domains: (1) the external domain (external sources and stimuli such as professional publications and professional development programs), (2) the personal domain (teachers’ knowledge and beliefs), (3) the domain of practice, and (4) the domain of consequence (salient outcomes). The interaction among these domains occurs through the processes of enactment and reflection. Professional development programs can be situated within the external domain, which, through interaction with teachers’ personal world (the personal domain, the domain of practice, and the domain of consequences), may contribute to desired changes in any of the above domains. Based on the analysis of four models of professional development (Guskey, 2002; Desimone, 2009; Clarke & Hollingsworth, 2002; Opfer & Pedder, 2011; Evans, 2014), Boylan et al. (2018) concluded that no single theoretical model of professional development is perfect. They argue that theoretical models are not so much representations of reality as tools that researchers and practitioners can use “to inform the design of research and evaluation of professional learning activities” (p. 18).

2.2. Key Characteristics of Effective Professional Development

M. M. Kennedy (1998) highlighted the potential effectiveness of professional development focused on student learning. Subsequent research has identified additional characteristics of effective professional development, emphasizing the importance of active teacher engagement, coherence, sustained duration, and collaboration (Desimone et al., 2002; Desimone & Garet, 2015), together with modeling, coaching, and opportunities for feedback and reflection (Darling-Hammond et al., 2017). These features constitute the consensus model of effective professional development (Hill et al., 2013; Roth et al., 2019). Although the features of this consensus model are often used in the design of professional development programs and in research, the supporting evidence remains inconsistent (Wilson, 2013), suggesting that they may not be reliable predictors of program effectiveness (M. M. Kennedy, 2016).

Collaboration, recognized as a core feature of effective professional development (Desimone & Garet, 2015), is most clearly manifested in professional learning communities (Stoll et al., 2012). According to Stoll et al. (2006), a professional learning community “suggests a group of people sharing and critically interrogating their practice in an ongoing, reflective, collaborative, inclusive, learning-oriented, growth-promoting way; operating as a collective enterprise” (p. 223). Professional learning communities enable teachers to cultivate a culture of mutual support aimed at enhancing student learning (Hamos et al., 2009). Although research has demonstrated positive effects of professional learning communities on teacher knowledge (Mu et al., 2018), teaching practices, and student learning outcomes (Doğan & Adams, 2018; Lomos et al., 2011), it remains crucial to determine how to foster collegial dialogue and reflection among teachers, provide high-quality guidance, and facilitate collaboration across schools.

Professional learning communities, both conceptually and practically, are intrinsically linked to “teacher collective efficacy—the shared beliefs of teachers within a school that they can collectively, significantly, and positively influence student learning” (Voelkel & Chrispeels, 2017, p. 2). Eells’s (2011) meta-analysis indicates that collective efficacy is a powerful influence on student learning outcomes (Donohoo et al., 2018).

Darling-Hammond et al. (2017) analyzed 35 effective professional development programs and found that 30 of them included some form of expert support. One type of expert support that has a particularly positive impact on teaching and student learning is one-on-one coaching (Kraft et al., 2018). Leadership grounded in interaction rather than hierarchical power and authority also plays an important role in promoting professional development (Poekert, 2012). This can be fostered through visionary and transformational leadership. According to Mourão (2018), “visionary leadership has been defined as a process with three specific steps: (1) vision (idea), (2) communication (word), and (3) empowerment (action)” (p. 128). In contrast, a transformational leader “acts in the creation of shared goals and encourages the experimentation of solutions, making concessions of power and maintaining a systemic communication that leads to collective engagement” (p. 129). A. B. Bakker et al. (2023) argue that transformational leaders do not steer their followers toward transformation but rather identify their strengths and encourage them to take initiative in driving change. In this context, teacher leadership is particularly important (Stone & Stone, 2024). York-Barr and Duke (2004) note that teachers who take on leadership roles are typically experienced, knowledgeable, hardworking, creative, and respected by colleagues. While these qualities may result from individual initiative, it is essential to explore how the competencies required of teacher leaders can be systematically cultivated to support professional development in both formal education and in-service contexts.

The use of classroom video recordings in teacher professional development has been steadily increasing (Gaudin & Chaliès, 2015; Major & Watson, 2018) because they facilitate teacher-to-teacher conversations about practice without requiring a physical presence in the classroom (Borko et al., 2014). Recent literature (Ciani et al., 2021; Marsh & Mitchell, 2014) highlights two key benefits of using videos in teacher training: the development of observation and analysis skills and the ability to reflect. Videos provide teachers with substantially more information about instruction, enabling deeper reflection and strengthening their understanding of “what to do” (Gaudin & Chaliès, 2015). In professional development contexts, participants often analyze both their own practice and that of their colleagues (Hamel & Viau-Guay, 2019). Teacher-led collaborative groups play an important role in this process by facilitating situated learning (Roth et al., 2017) as they analyze and reflect on their own videos (Beisiegel et al., 2018). However, although video-based continuing professional development (CPD) supports collaborative discussions about teaching, it does not necessarily lead to improved outcomes unless it is carefully planned and effectively implemented (Seago et al., 2018; Tekkumru-Kisa & Stein, 2017).

Online professional development has changed substantially over the past two decades (Curtis, 2017), with its importance becoming particularly evident in times of crisis. In epidemic contexts where indoor gatherings are restricted or prohibited, online professional development is especially critical (Assunção Flores & Gago, 2020). Web-based technologies enable the delivery of professional development online, facilitating teacher participation and reducing associated costs. A recent meta-analysis confirmed the positive impact of online teacher professional development on teachers’ and students’ learning, as well as on classroom practice (Morina et al., 2025). It also found that synchronous formats are more effective than asynchronous formats in promoting student outcomes. Despite the growing availability and acceptance of online professional development programs—whether delivered partially or fully online—they have been found to be equally effective (Li et al., 2023) or less effective (Lynch et al., 2019) than traditional face-to-face delivery. It remains unclear whether this relative ineffectiveness stems from the absence of face-to-face interaction or from other barriers such as inadequate implementation, insufficient training, or participants’ technological readiness. With further technological advances, continued scientific research, adequate training of both participants and facilitators, and the adoption of blended models (Macià & García, 2016), online professional development could become a common and effective practice.

2.3. Characteristics of Effective Science Teacher Professional Development Programs

To identify the characteristics of effective professional development programs for science teachers, we conducted a systematic literature review prior to this study (Mirosavljević & Bognar, 2019). Based on an analysis of experimental studies that reported practically significant effect sizes on student learning outcomes, we drew the following conclusions regarding the design and implementation of effective professional development programs for science teachers:

During initial professional development, teachers should have opportunities to become familiar with the key characteristics of high-quality science instruction. This can be achieved through initial professional workshops. To support the learning of new instructional methods, teacher manuals and classroom video recordings featuring more experienced teachers can be used (Taylor et al., 2017). Initial professional workshops are most effective when conducted face-to-face, as this format enables direct discussion with facilitators and peer-to-peer exchange about key aspects of instructional improvement—interactions that are more difficult to achieve in online environments (Lynch et al., 2019).

During the implementation of the intervention, teachers can be supported through meetings of learning communities scheduled throughout the school year (Taylor et al., 2017), where they can engage in reflective discussions about implemented changes, experiences, ideas, uncertainties, questions, and examples from practice (Doppelt et al., 2009; Johnson & Fargo, 2014; Nugent et al., 2016). These learning communities can also be organized online using learning management systems, Facebook groups, and asynchronous platforms (Sümer, 2021). Reflective discussions may be grounded in classroom video recordings.

To achieve complex instructional changes, teachers require guidance and support (Basma & Savage, 2018). Facilitators provide support by giving feedback based on classroom observations and responding to teachers’ questions throughout the professional development process (Helf & Cooke, 2011), and may be members of the research team (Penuel et al., 2011) or experienced teachers and local experts (Bush, 1984). When preparing teacher leaders, it is beneficial for them to participate in the same professional development program that they will later help facilitate (Heller et al., 2012).

Given that teaching is a complex process, it is necessary to consider the combination of multiple factors that simultaneously influence teacher learning, student learning, instructional change, and improvements in educational outcomes. This requires a structured approach that includes high-quality professional development, ongoing support and feedback for teachers during the implementation of changes, and instructional materials for both teachers and students (Snilstveit et al., 2015).

It is important to emphasize that changes can lead to improved student educational outcomes only if they involve instructional changes that enable higher-quality student learning. For this to happen, professional development must promote learning grounded in coherent and scientifically validated principles (Hattie, 2012). This requires instruction based on clearly defined goals and authentic, challenging problems, and instruction that encourages students to ask questions, investigate, think, and draw conclusions (Taylor et al., 2017), as well as to engage in collaborative learning and scientific and metacognitive thinking (Greenleaf et al., 2011).

The professional development program for science teachers, Science Teachers Learning through Lesson Analysis (STeLLA), implemented in the United States (Taylor et al., 2017; Roth et al., 2019), exemplifies these conclusions. The program supported teachers’ professional learning and aimed to deepen their science content knowledge, enhance their pedagogical content knowledge, develop reflective skills for analyzing teaching and student learning, and promote the application of content and pedagogical knowledge in science lesson planning. To achieve these goals, facilitators prepared plans for six lessons that teachers studied during summer workshops and later implemented in their teaching practice in the autumn. During the winter, teachers planned their instruction according to principles organized into two groups: (a) strategies for eliciting, supporting, and advancing student thinking, and (b) strategies for designing coherently structured science content. The program concluded with the implementation of lessons independently prepared by the teachers within school-based study groups. The level of facilitation, teacher reflection, and use of classroom videos varied across program stages. In the initial phase, teacher learning was strongly guided and supported through classroom videos featuring experienced teachers. In the autumn phase, the focus shifted to discussions of classroom videos produced by participating teachers, with facilitators supporting deeper analysis and observation protocols guiding discussion. In the third phase, facilitators’ support was substantially reduced, allowing teacher autonomy and ownership of planning, implementation, and instructional analysis to become more prominent.

3. Materials and Methods

3.1. Research Sample

The study employed a quasi-experimental design involving an experimental group and a control group. The participants were biology teachers and their eighth-grade students (

Table 1. Number of Students in the Control and Experimental Groups.

	Initial Test	Final Test
Number of students in the control group	347	380
Number of students in the experimental group	248	241
Total	595	621

). A total of 595 students completed the initial test in January 2022 (347 in the control group and 248 in the experimental group). From February to the end of May 2022, the seven teachers in the experimental group participated in a professional development program, while the thirteen teachers in the control group attended regular professional meetings and conducted their lessons as usual. In June 2022, the final test was administered and completed by 621 students (380 from the control group and 241 from the experimental group).

After receiving approval from the Ethics Committee of the Faculty of Humanities and Social Sciences, J. J. Strossmayer University of Osijek, the research team began informing and recruiting teachers to participate in the experimental study. Based on a list of primary schools in the eastern part of Croatia, 20 schools were randomly selected for the experimental group and another 20 for the control group. Biology teachers employed in these schools were informed in writing about the aims of the study and the procedures for participation. In the experimental group, seven teachers agreed to participate, while thirteen teachers did so in the control group. The teachers informed students’ parents in writing and obtained their written consent for classroom video recording and participation in the study.

3.2. Biology Teacher Professional Development Program

The professional development program examined in this study was part of a research project consisting of four phases:

(1)

Conducting systematic literature reviews to examine the characteristics of effective biology instruction and effective professional development for biology teachers, which informed the design of the professional development program;

(2)

Implementing and evaluating the professional development program through action research, with prominent biology teachers participating alongside members of the research team;

(3)

Conducting an experimental study to determine the effectiveness of the professional development program with respect to student learning outcomes;

(4)

Disseminating and popularizing the project results.

This study was conducted during the third phase of the project. The experimental professional development program included elements based on the characteristics of effective teacher professional development outlined in Section 2.3. It began with two initial training sessions, each lasting five hours. These sessions introduced teachers to the modalities of collaboration, the expected changes in teaching, and the e-learning approach. The training was facilitated by members of the research team and biology teachers who had previously completed the same program.

After the initial training in October and November 2021, the research team recorded the lessons of all participating teachers before implementing instructional changes. Subsequently, members of the research team visited the teachers in their classrooms on two additional occasions during the second semester to record their teaching practices and discuss instructional changes and professional development activities. These video recordings were later used for reflection during online learning community sessions, in which all teachers in the experimental group participated. Reflective discussions within the online learning communities took place in a collaborative and collegial atmosphere. The sessions were held twice a month, each lasting two hours, over a 12-week period via Zoom.

Additionally, a Moodle forum was created for each teacher, where videos of their lessons were posted. Through these forums, biology teachers received written feedback on their teaching and student learning. The feedback was provided exclusively by the first author, who analyzed each recorded lesson using the TOF (Bezinović et al., 2012), a nationally developed instrument designed for the systematic analysis of classroom instruction in the Croatian educational context, with clearly defined observational indicators and scoring criteria. The written feedback was individualized for each teacher and focused on identifying strengths in teaching practice, followed by specific, actionable suggestions for improvement. In this way, teachers received continuous support and feedback throughout the implementation of changes.

To prepare their lessons, teachers used a handbook co-authored by the first and third authors of this paper. The handbook contained thematic units, macro-concepts, and learning outcomes prescribed in the official biology curriculum. Special emphasis was placed on changes in teaching practices and student learning. The lessons were structured to promote student engagement, cooperative learning, inquiry, authentic problem solving, critical and creative thinking, and the application of metacognitive strategies.

3.3. Video Analysis

During the study, the teaching practice of each teacher in the experimental group was recorded three times. The first recording was conducted before the professional development program, the second during the program, and the third after its completion. For the research analysis, the same TOF ratings completed during the program by the first author were used, while the third author independently analyzed the same recorded lessons using the same instrument. Both researchers had prior experience with the TOF from earlier phases of the project, which further supports the reliability of the observational procedure. This process resulted in two independent sets of TOF ratings for each recorded lesson (see

Table 2. Analysis of mean assessor ratings of teaching features for all teachers—initial to final phase of professional development.

Teaching Features According to the TOF (Bezinović et al., 2012)	Differences Between Recordings
	1st–2nd	2nd–3rd	1st–3rd
Classroom climate	−1%	13%	12%
The teacher treats students with respect and acceptance.	0%	0%	0%
A relaxed working atmosphere prevails in the classroom.	0%	0%	0%
The teacher praises students’ effort and achievement.	46%	18%	64%
The teacher maintains good nonverbal communication with students.	11%	−4%	7%
The teacher uses appropriate humor in class.	21%	39%	61%
The teacher responds readily to students’ questions.	−68%	57%	−11%
Students follow classroom rules.	11%	−4%	7%
The teacher responds effectively to inappropriate student behavior.	−32%	0%	−32%
Lesson structuring	4%	7%	11%
At the beginning of the lesson, the teacher clearly states the topic.	−25%	21%	−4%
The teacher clearly states the lesson objectives (learning outcomes).	21%	25%	46%
The teacher gives clear instructions and asks clear questions.	0%	0%	0%
During the lesson, students know what they are expected to do.	0%	−7%	−7%
The teacher explains progressively, making logical transitions from simpler to more complex content.	7%	−4%	4%
Various purposeful activities alternate during the lesson.	18%	0%	18%
The teacher directs students’ attention to key concepts and essential content.	−25%	32%	7%
The teacher monitors students’ reactions and adjusts the timing of transitions between activities.	11%	−4%	7%
The lesson is fully filled with activities (no “idle time”).	14%	0%	14%
The teacher briefly summarizes the lesson at the end.	11%	32%	43%
The lesson is interactive (many questions and answers).	−14%	−11%	−25%
The lesson is well structured and thoroughly prepared.	25%	0%	25%
Student engagement and motivation	16%	15%	31%
Students are actively engaged in the lesson.	18%	0%	18%
Students collaborate with one another.	36%	0%	36%
Students participate with interest.	25%	4%	29%
Students freely express their ideas, ask questions, or seek clarification.	0%	43%	43%
The teacher encourages students to provide their own examples related to the lesson content.	4%	29%	32%
Individualization/differentiation of instruction	−8%	7%	−1%
The teacher assigns tasks of varying difficulty according to students’ abilities or interests.	0%	0%	0%
The teacher provides additional instructions, explanations, or time for some students.	−29%	25%	−4%
The teacher re-explains or uses a different approach if some students do not understand or answer incorrectly.	−46%	−11%	−57%
The teacher allows sufficient time for students to answer questions.	−7%	18%	11%
The teacher offers choices in activities or working methods.	−11%	14%	4%
The teacher involves students who do not volunteer or participate in class activities.	29%	−7%	21%
The teacher ensures that certain students do not dominate discussions or activities.	11%	11%	21%
Teaching of metacognitive skills and learning strategies	−1%	17%	16%
The teacher emphasizes understanding rather than rote memorization.	29%	0%	29%
The teacher asks questions that stimulate higher-order thinking.	29%	0%	29%
The teacher explicitly teaches students how to approach learning, solve tasks, or practice.	0%	46%	46%
The teacher encourages students to explain in their own words how they understood the lesson content.	−11%	54%	43%
The teacher asks students to describe and explain the steps they used in solving a task.	0%	0%	0%
The teacher encourages students to monitor and check their own work (e.g., identify and correct mistakes, verify solutions).	14%	32%	46%
The teacher asks students to evaluate their own work and progress.	0%	11%	11%
The teacher encourages students to provide personal opinions and critical reflections on lesson content.	−43%	14%	−29%
The teacher connects lesson content with examples from everyday life and students’ prior knowledge and experiences.	−4%	−7%	−11%
The teacher assigns tasks that allow application of knowledge or skills to everyday situations.	7%	0%	7%
The teacher encourages students to take notes and organize content independently (e.g., highlighting main ideas, creating diagrams).	−14%	57%	43%
The teacher promotes connections between different subjects.	−18%	0%	−18%
Feedback and formative assessment	−8%	20%	13%
The teacher asks questions to check student understanding.	0%	4%	4%
The teacher provides specific feedback on students’ work.	−18%	64%	46%
The teacher explains in a timely manner why an answer is correct or incorrect.	7%	−11%	−4%
The teacher explains evaluation criteria and expectations using concrete examples.	0%	29%	29%
The teacher emphasizes students’ progress and success rather than shortcomings.	−18%	14%	−4%
The teacher prepares questions or tasks in advance to check students’ understanding.	−18%	21%	4%

Note. The six categories encompassing different teaching features are shown with a dark background and white font. Positive changes greater than 10% are shaded in gray, while negative changes below −10% are presented in bold italics. For the initial lesson, Cohen’s kappa indicated moderate agreement between raters (κ = 0.418, 95% CI [0.267, 0.569], p < 0.001); for the second lesson, Cohen’s kappa indicated almost perfect agreement (κ = 0.826, 95% CI [0.718, 0.934], p < 0.001); and for the third lesson, Cohen’s kappa indicated substantial agreement (κ = 0.635, 95% CI [0.496, 0.774], p < 0.001).

). Each researcher independently rated all teaching features for each video as 0 (not present), 0.5 (partially present), or 1 (fully present). Inter-rater reliability was assessed using Cohen’s kappa coefficient, which ranges from 0 (no agreement) to 1 (perfect agreement). Landis and Koch (1977) classified values as indicating poor agreement (0.20 or below), fair agreement (0.21–0.40), moderate agreement (0.41–0.60), good agreement (0.61–0.80), and very good agreement (0.81–1.00).

For each feature, the sum of all scores assigned by each researcher across the videos of all seven teachers was first calculated. The average of the two sums was then computed to provide a more consistent and objective measure of the presence of each feature. This yielded a score between 0 and 1 for each item. To illustrate the changes in teaching practice, the mean score from the first recording was subtracted from the mean scores of the second and third recordings. The resulting values were multiplied by 100 to express the change as a percentage. Values greater than 10% were interpreted as progress, values between −10% and 10% indicated stability, and values lower than −10% signified regression.

3.4. Instruments and Their Validation

Student performance was assessed using a pretest (administered before the implementation of the professional development program) and a posttest (administered after implementation), both developed specifically for this study. The test items were developed by the third author in collaboration with a biology teacher who participated in the second project phase, conducted prior to this research, based on the biology curriculum as well as the thematic units and learning outcomes addressed during the professional development program. The final version of the tests was reviewed by an additional member of the research team with expertise in biology to ensure content accuracy and alignment with curricular outcomes. Each written test consisted of tasks distributed across three cognitive levels according to Crooks’s (1988) revision of Bloom’s taxonomy: (1) reproduction and literal comprehension, (2) conceptual understanding, and (3) application and problem solving. In both tests, students could achieve a maximum of 2.5 points at the first cognitive level, 16 points at the second level, and 6.5 points at the third level, for a total of 25 points. The allocation of points across cognitive levels followed the recommendations of Begić et al. (2016), who suggest that in constructing biology assessments, tasks assessing higher-order cognitive processes should receive more points than those targeting lower cognitive levels.

The test was first piloted in a preliminary study on a separate student sample. Items that did not meet psychometric criteria, as determined by analyses of the item difficulty index (P) and item discrimination index (D), were excluded from the final version. At this stage, Cronbach’s alpha was 0.95 for the pretest and 0.90 for the posttest, indicating high reliability of the instrument (L. Cohen et al., 2018; Taber, 2018).

3.5. Statistical Data Analysis

Students’ overall performance on the written knowledge tests was summarized using descriptive statistics. Differences in performance between the experimental and control groups on the initial and final knowledge tests were examined using independent-samples t-tests. In addition to overall performance, t-tests were conducted separately for each of the three cognitive task levels to identify differences in achievement across levels of cognitive complexity. All comparisons were conducted within each cognitive level using identical scoring criteria for the experimental and control groups, and no direct comparisons were made across cognitive levels. The Kolmogorov–Smirnov test was used to assess the normality of the data distribution, and Levene’s test was used to verify the homogeneity of variances. In addition to significance testing, Cohen’s d effect size was calculated for overall performance and for each cognitive level. Statistical analyses were conducted using IBM SPSS Statistics (Version 29; IBM Corp, 2022), with the significance level set at α = 0.05.

A stepwise multiple linear regression analysis was conducted to examine the predictive power of participation in the professional development program and prior knowledge (pretest) on student performance, aiming to identify differences in student achievement between the experimental and control groups overall and across cognitive levels (second and third research questions). The analysis assessed the extent to which each predictor, individually and combined, explained variability in students’ posttest scores. In all analyses, the dependent variable was student performance on the posttest, measured as (1) the total test score and (2) the number of points achieved at each of the three cognitive levels. The independent variables were group membership (experimental or control), representing participation in the professional development program, and pretest scores (both total scores and scores at each of the three cognitive levels).

4. Results

This section presents the results in three parts: (1) an analysis of changes in teaching before and after the professional development program, (2) a comparison of student achievement between the experimental and control groups, and (3) a regression analysis of the contribution of the implemented professional development program to student outcomes.

4.1. Teaching Analysis

Table 2 presents the results of the assessment of teaching features obtained using the (Bezinović et al., 2012) to focus on key aspects of the expected changes (Table 2). Within the classroom climate category, among the eight observed characteristics, the greatest improvements were noted in teachers’ praise of students’ effort and achievement (64%) and in the use of appropriate humor in class (61%). However, it was found that teachers were slightly less responsive to students’ questions (−11%) and less active in addressing inappropriate behavior (−32%), since such behavior was not observed in the video recordings.

In the category of lesson structuring, positive changes were observed in four of the twelve features. These were most evident in the clear formulation of lesson objectives and learning outcomes (46%) and in the summarizing of lesson content at the end of the lesson (43%). In addition, lessons were better structured and prepared (25%), included a greater variety of purposeful activities (18%), and showed less “idle time” (14%). At the same time, observers noted that lessons were less interactive (−25%).

Changes were also observed in all five features related to student engagement and motivation. These included students’ free expression of ideas, questions, and requests for clarification (43%); cooperative learning (36%); teachers’ encouragement of students to provide their own examples (32%); student interest (29%); and active participation in class (18%).

Several changes were also noted in the area of individualization and differentiation. Teachers made greater efforts to include less active students (21%) and to ensure that certain students did not dominate classroom activities (21%). They also allowed students somewhat more time to answer questions (11%). However, it was observed that teachers were less likely to re-explain or re-present content when some students did not understand or gave incorrect answers (−57%).

Regarding the teaching of metacognitive skills and learning strategies, the observed changes were largely positive. Teachers increasingly encouraged students to monitor and check their own work (46%) and to take notes and organize content independently (43%). Teachers provided more explicit instruction on approaches to learning, problem solving, and practice (46%) and encouraged students to articulate their understanding of the content in their own words (43%). They also posed more questions to stimulate higher-order thinking (29%) and placed greater emphasis on conceptual understanding (29%). Furthermore, teachers were slightly more likely to ask students to evaluate their own work and progress (11%). On the other hand, observers found that teachers were less likely to encourage students to express personal opinions and provide critical reflections on lesson content (−29%), make cross-curricular connections (−18%), or relate lesson content to everyday examples and their prior knowledge and experiences (−11%).

In the area of feedback and formative assessment, no major changes were found for three of the features. However, teachers provided more specific feedback to students (46%) and explained their assessment criteria more frequently using concrete examples (29%).

A comparison of the first and last recordings revealed predominantly positive changes, particularly greater student engagement and motivation (31%), increased emphasis on metacognitive skills and learning strategies (16%), improvements in feedback and formative assessment (13%), a more positive classroom climate (12%), and better lesson structuring (11%). With respect to the first research question, it can be concluded that the professional development program led predominantly to positive changes in biology instruction, although some negative changes were also observed.

4.2. Analysis of Student Performance

In addressing the second research question, the analysis focuses on whether students in the experimental group outperformed their peers in the control group on the biology test. This was examined by analyzing the pretest and posttest results.

In both the pretest and the posttest, the maximum possible score was 25 points. On the pretest, students in the experimental group obtained an average of 13.22 points, while students in the control group obtained an average of 12.68 points. The minimum score in the experimental group was 4.5 points, compared to 2.5 points in the control group. The maximum score was 22 points in the experimental group and 21.5 points in the control group. In the experimental group, 25% of students scored 11 points or fewer, whereas 25% scored 15.5 points or more. In the control group, 25% of students scored 10 points or fewer, and 25% scored 15.5 points or more (Figure 2). No statistically significant difference was found between the experimental and control groups on the pretest, t(593) = 1.70, p = 0.09.

On the final test, students in the experimental group achieved a mean score of 9.8 (out of 25), compared to 8.9 in the control group. Experimental group scores ranged from 0 to 18.5, with 25% of students scoring ≤ 7.5 and 25% scoring ≥ 11.5. Control group scores ranged from 0 to 17, with 25% scoring ≤ 6.5 and 25% scoring ≥ 11.5 (Figure 3). Students in the experimental group performed significantly better than those in the control group, t(593) = 3.19, p = 0.002, d = 0.26.

Table 3. Descriptive statistics for the final written knowledge test of students in the experimental and control groups, by question level.

	First-Level Questions		Second-Level Questions		Third-Level Questions
	Experimental Group	Control Group	Experimental Group	Control Group	Experimental Group	Control Group
N	241	380	241	380	241	380
M	0.89 *	0.74 *	6.43 *	5.89 *	2.49 *	2.27 *
Median	1	1	6.5	6	2.5	2
SD	0.65	0.67	2.57	2.50	1.18	1.29
Min.	0	0	0	0	0	0
Max.	2.50	2.50	14	12.5	5.5	6
25th percentile	0	0	5	4	1.5	1.5
75th percentile	1	1	8	7	3.5	3

* p < 0.05.

presents the results by cognitive task level in the final test. On first-level questions, experimental group students (M = 0.89, SD = 0.65) scored significantly higher than controls (M = 0.74, SD = 0.67), t(593) = 2.73, p = 0.006, d = 0.22. On second-level questions, experimental group performance (M = 6.43, SD = 2.57) also exceeded that of the control group (M = 5.89, SD = 2.50), t(593) = 2.59, p = 0.010, d = 0.21. On third-level questions, experimental group students (M = 2.49, SD = 1.18) again outperformed controls (M = 2.27, SD = 1.29), t(593) = 2.18, p = 0.030, d = 0.17.

The regression analysis was first conducted to examine the contribution of the professional development program and prior knowledge (pretest) in explaining overall student performance on the posttest. The model was statistically significant, F(1, 593) = 10.15, p < 0.001, accounting for 1.7% of the variance (R² = 0.017). The professional development program emerged as a significant predictor (β = 0.130, p < 0.001), whereas pretest performance did not significantly predict overall posttest results (see

Table 4. Results of stepwise regression analysis predicting total posttest score.

Model	β	R2	F
Professional development program	0.130	0.017	F(1, 593) = 10.15 **

** p < 0.01.

).

The analysis was then extended to posttest performance across different cognitive levels. The professional development program again emerged as a statistically significant predictor for first-level questions (β = 0.106, p < 0.001), explaining 1.1% of the variance (R² = 0.011). It was also a significant predictor for second-level questions (β = 0.102, p < 0.001), accounting for 1.0% of the variance (R² = 0.010), and for third-level questions (β = 0.084, p < 0.001), explaining 0.7% of the variance (R² = 0.007; see

Table 5. Results of stepwise regression analysis predicting posttest scores by cognitive level.

Question Level	Model	β	R2	F
First level	Professional development program	0.106	0.011	F(1, 593) = 6.79 **
Second level	Professional development program	0.102	0.010	F(1, 593) = 6.21 **
Third level	Professional development program	0.084	0.007	F(1, 593) = 4.19 **

** p < 0.01.

). In contrast, pretest performance at the different cognitive levels was not a significant predictor of posttest performance at the corresponding levels.

5. Discussion

The findings regarding the first research question suggest that the professional development program contributed to predominantly positive changes in biology instruction. Of the 50 observed features of teaching practice, 24 improved by more than 10%, nine changed by up to 10%, seven declined by more than 10%, and five declined by up to 10%. These results address the first research question and support the first hypothesis, indicating that participation in the professional development program was associated with measurable changes in classroom practices.

Students in the experimental group also outperformed their peers in the control group on the posttest, confirming the effectiveness of the professional development program and addressing the second research question. This finding is consistent with the second hypothesis, which predicted statistically significant differences in achievement favoring students taught by teachers who participated in the professional development program.

The third research question examined performance differences across cognitive levels of the test. Posttest results showed that experimental group students, on average, achieved higher scores at all three levels. Effect sizes decreased as cognitive complexity increased (first level: d = 0.22; second level: d = 0.21; third level: d = 0.17), a pattern that may be due to greater variability in performance on more complex tasks (Begić et al., 2016).

Regression analysis provided additional insights into the contribution of the professional development program to posttest performance across cognitive task levels. The model was a significant predictor of performance both overall and at each level, including the third (β = 0.084, p < 0.001). Although the variance explained was modest (R² = 0.007), prior knowledge (pretest) was not a significant predictor of achievement, underscoring the role of instructional changes resulting from the professional development program. These results further support the third hypothesis, indicating that the effects of the professional development program were evident across different cognitive levels of the assessment.

5.1. The Professional Development Program in Relation to Existing Approaches

A. Kennedy (2005) categorized professional development models into three main types: transmission, transitional, and transformative. The primary distinction among these categories lies in the degree of teacher autonomy: “This categorisation and organisation of CPD models … suggests increasing capacity for teacher autonomy as one moves from transmission, through transitional to transformative categories” (p. 248). In our program, the use of a handbook to guide instruction corresponds to the transmission category, while teachers’ participation in a community of practice reflects elements of the transitional category. Because the intervention was relatively short, we recognized that it would be difficult for teachers to independently design and implement instructional changes based solely on the information provided during the professional development program (Fitzgerald et al., 2019). Consequently, we offered a learning model similar to the first two phases of the STeLLA program (Taylor et al., 2017), in which teachers initially analyzed lessons taught by more experienced colleagues and then “taught the science content to their students using the STeLLA program lesson plans and met monthly in 4 h sessions with their study groups to analyze video clips and student work from one another’s enactment of the STeLLA lesson plans” (Roth et al., 2019, p. 1228). In our program, video analysis also played a central role. Lamkin and Nesloney (2018) argue that guided self-reflection using video encourages teachers to evaluate the quality of their own learning, enabling them to adopt new teaching strategies and monitor student learning. Nugent et al. (2016) likewise emphasize that video supports teacher self-reflection and helps identify both strengths and areas for improvement in classroom practice.

In our program, online reflective communities of practice allowed teachers to recognize changes in their own practice and to reflect on their meaning and value for biology teaching, similar to the Lesson Study approach, which involves collaborative analysis and reflection following a lesson (Ventista & Brown, 2023). According to McChesney and Aldridge (2021), professional development has a genuine impact only when teachers consider it relevant and valuable to their daily practice—a condition fostered by reflecting on changes in teaching and student learning. In online learning communities, teachers reflected on both their instructional practices and student learning, aiming to better understand how students learn and the challenges they face. This aligns with Hattie’s (2012) suggestion that teachers should “focus on seeing learning through the eyes of the students, appreciating their fits and starts in learning, and their often non-linear progressions to the goals…” (p. 19).

Although previous studies have shown no clear advantage of online professional development compared to face-to-face approaches (Lynch et al., 2019; Li et al., 2023), our program included an online community of practice where teachers and researchers reflected on lesson videos every two weeks. This fostered situated and sociocultural learning (Kelly, 2006; Vygotsky, 1978; Wenger et al., 2002), which in turn led to changes in teaching practice. Teachers also had access to all lesson recordings and received feedback from members of the research team, including lesson analyses conducted using the TOF. The facilitators’ role extended beyond offering advice; they engaged collaboratively with teachers in discussions, data interpretation, and addressing specific instructional challenges. This type of partnership is recognized in the literature as a form of transformative collaboration between teachers and the academic community (Wang & Wong, 2019).

While the long-term sustainability of such a program is difficult to assess, its elements indicate potential for the development of professional learning networks, which Poortman et al. (2022) define as “a group of educators (e.g., teachers, school leaders, possibly in collaboration with researchers, and/or policy-makers) coming together with others outside of their everyday community of practice with the intention of engaging in collaborative learning to improve outcomes for students” (p. 107).

5.2. The Impact of the Professional Development Program on Changes in Teaching and Student Achievement

This study demonstrated the positive impact of professional development for biology teachers on classroom practice (Table 2) and student achievement on the posttest (Figure 3 and Table 3), while prior knowledge, as measured by the pretest, showed little effect (Figure 2). Although students in the experimental group outperformed those in the control group, the effect size was relatively small (d = 0.26) according to J. Cohen’s (1988) benchmarks (0.20 = small, 0.50 = medium, 0.80 = large).

However, A. Bakker et al. (2019) recommend avoiding arbitrary interpretations of effect sizes. Instead, they suggest relating research results to comparable studies with similar characteristics (research design, sample size, type of measurement, type of variable influenced, etc.) (p. 7). In line with this recommendation, the interpretation of the effect size obtained in this study focuses on the research design, type of instrument, sample size, and comparisons with findings from meta-analytic studies on professional development.

Some studies (A. Bakker et al., 2019; Cheung & Slavin, 2016; Lipsey et al., 2012) have reported larger effects in quasi-experimental designs employing researcher-developed instruments. Cheung and Slavin (2016) found that the mean effect size of quasi-experimental studies evaluating reading, mathematics, or science programs aimed at improving student achievement was 0.23, while the average effect size of studies using researcher-developed instruments was 0.40. From a research design perspective, the effect size obtained in the present study is average; however, regarding the type of instrument used, it is below average. According to the same authors, studies with large samples (n > 250) report an average effect size of 0.16. In the present study, the sample size was approximately 600 students, indicating that the observed effect size was above average.

It is important to note that, in this case, the professional development program was the most distal variable in the chain of influence on students’ learning outcomes (Asterhan & Lefstein, 2024). Even when teacher learning and instructional practice improve, such changes do not always translate into higher student achievement (Yang et al., 2020; Yoon et al., 2007), and when they do, the gains are often modest (Fischer et al., 2018). Sims et al. (2025), in a recent meta-analysis of professional development effects on student achievement, reported an average effect size of only 0.05. They argued that effective programs must provide insights into the features of effective teaching and learning, motivate teachers to change their practice, offer techniques for implementing these insights, and make the change a routine part of practice. In our program, the initial workshops and professional learning communities provided teachers with insights into the characteristics of effective biology instruction and motivated them to initiate change. These changes involved inquiry-based learning, in which students asked questions, investigated problems, and constructed knowledge through analysis and discussion, with the teacher serving as a guide (Pedaste et al., 2015); the flipped classroom, where students acquire introductory content at home (e.g., through videos) and apply it in class through deeper learning tasks such as problem solving and discussion (Bergmann & Sams, 2012); and cooperative learning, where knowledge is developed through peer interaction, idea exchange, and collaborative problem solving (Gillies, 2016). Beyond insights and motivation, teachers also received handbooks with pre-designed lesson plans containing concrete techniques, whose implementation was monitored using the TOF and through reflective online discussions in learning communities. Analysis of video recordings with the TOF (Table 4) showed that teachers largely implemented these changes in practice. This suggests that our program incorporated all four elements of effective professional development.

When comparing the effect size achieved in this study (d = 0.26) with the average effect size (d = 0.15) reported by Sims et al. (2025) for programs containing all four elements, our intervention appears somewhat more effective. However, compared with the average effect size (d = 0.36) calculated by Slavin et al. (2014) in their best-evidence synthesis, our result was slightly weaker.

Although our professional development program produced observable changes in teaching, not all changes were positive. Several TOF indicators related to classroom interaction and adaptive instruction showed declines exceeding the predefined threshold, including teachers’ responsiveness to students’ questions, use of alternative explanations when students did not understand, and encouragement of personal opinions, real-life connections, and interdisciplinary links (Table 2).

These instructional practices rely heavily on spontaneous pedagogical decision-making and instructional flexibility. When teachers are simultaneously adopting new, structured approaches and focusing on implementing cognitively demanding tasks, opportunities for open-ended interaction and immediate instructional adaptation may be temporarily reduced.

Such patterns are consistent with the concept of an implementation dip (Fullan, 2003), in which the introduction of new practices may initially result in lower-than-expected performance. This may be attributed to the fact that the new practices had not yet been fully internalized as part of teachers’ professional repertoire. Moreover, the changes were implemented with a high level of external support, suggesting that full autonomy in applying the new instructional approaches had not yet been achieved.

Moreover, the development of students’ abilities related to higher cognitive levels (e.g., prediction, questioning, inquiry, application of knowledge, problem solving, cooperative and metacognitive skills) requires time. Because the posttest was conducted immediately after the 12-week professional development program, students may not yet have reached the stage of automatization of more cognitively demanding processes. Thus, the observed improvements in lessons do not necessarily mean that most students had developed a deeper understanding or were able to solve more complex tasks.

Finally, although carefully designed, the posttest could not capture all the effects of instructional changes, particularly those related to the development of metacognition, collaboration, and authentic problem solving. It is possible that students made progress in areas not accurately measured by the test.

6. Conclusions

This study shows that the implemented professional development program for biology teachers led to improvements in instructional practice, particularly by increasing student engagement and motivation to learn. However, not all TOF indicators showed positive trends, highlighting the need to extend the duration of professional development so that teachers can develop the full range of professional competencies required for the spontaneous facilitation of interactive instruction. Although student achievement in the experimental group was somewhat higher than in the control group, the effect sizes were modest, especially for tasks requiring higher-order cognitive skills. Nonetheless, this outcome exceeds the average effect size reported in comparable professional development programs (Sims et al., 2025). These findings indicate that even relatively short professional development initiatives can produce statistically significant gains in student achievement.

This study makes a scientific contribution by empirically validating a professional development program that integrates curriculum-aligned instructional materials, reflective video analysis using the TOF, and participation in online communities of practice. The study contributes to the understanding of the complex relationship between changes in instructional practice and student achievement, highlighting both the time required for teachers to internalize new approaches and the importance of adopting a multidimensional framework for evaluating educational interventions.

7. Limitations and Recommendations for Future Research

While this study demonstrated improvements in classroom practice and modest gains in student achievement, several limitations must be noted: First, both instructional changes and the impact of professional development on student learning were assessed only in the period immediately following the intervention. Future research should therefore employ delayed measures of student outcomes to evaluate knowledge retention and to identify which instructional changes teachers maintain over time. In the present study, such follow-up was not possible because the participants were eighth-grade students completing the final year of primary education in Croatia. After the intervention, students moved to different secondary schools, introducing substantial variability in instructional conditions, curricula, and learning environments. This heterogeneity makes it difficult to attribute longer-term learning outcomes solely to the professional development intervention. Future studies could address this limitation by recruiting students from lower grade levels, where longitudinal tracking within a more stable school context would be more feasible and would allow for a more robust examination of the sustainability of instructional changes and their effects on student learning.

Second, while teachers implemented changes in their instruction, they did so using pre-prepared lesson plans and with substantial external support. This reflects the transmission level of professional development, characterized by limited teacher autonomy (A. Kennedy, 2005). Future studies should examine how teachers develop greater autonomy in the long-term application of new instructional approaches and how such autonomy influences student learning.

Finally, although the instruments used in this study were carefully designed and aligned with curriculum outcomes, they may not have fully captured all dimensions of student learning, particularly those involving metacognition, collaboration, and authentic problem solving. Developing more sophisticated assessment tools to evaluate higher-order cognitive processes remains an important direction for future research.