Introduction

In the context of global interconnectivity, English proficiency serves as a crucial cornerstone of international discourse in diverse fields, including commerce, diplomacy, and cultural exchange (Ahmadi, 2018; Al-khresheh et al., 2020). The widespread recognition of English as a lingua franca has spurred an unparalleled emphasis on linguistic proficiency within diverse geopolitical landscapes, most notably in English as a Foreign Language (EFL) contexts, such as the Kingdom of Saudi Arabia (Alizadeh, 2016; Getie, 2020; Mardievna et al., 2020; Wright, 2019).

The increasing demand for English-language acumen within the Saudi Arabian ambit has been met with substantial institutional commitments, underscored by the government’s significant investments in English-language pedagogy, a testament to the language’s perceived transformative potential (Al-khresheh, 2021; Al-Oqaily and Salam, 2022). As English proficiency becomes increasingly synonymous with educational and socioeconomic mobility, dissecting the multifaceted dimensions of language learning becomes imperative.

At the forefront of these dimensions is the construct of self-efficacy, which posits a belief in one’s capability to achieve intended outcomes and has emerged as a pivotal influence on learner engagement and perseverance (Hashwani, 2008; Liu et al., 2023). Concurrently, the ascendancy of digital pedagogy, epitomized by the Blackboard management system, has ushered in an era of interactive and immersive educational experiences (Erben et al., 2008; Motlhaka, 2020).

Despite the acknowledged importance of self-efficacy and the advent of digital pedagogical tools, their confluence and their consequent impact on EFL outcomes in the Saudi context still need to be empirically explored. This lacuna underscores the need for methodological inquiry into the nexus between self-efficacy, technological integration, and language-learning efficacy. The importance of elucidating this tripartite relationship is multifaceted, with the potential to augment language-education methodologies, inform policy formulation, and optimize resource allocation within the educational sector of Saudi Arabia.

In response to this demand, the present study endeavors to construct and validate a structural model that delineates the correlation between self-efficacy and technological integration and their collective impact on English-language learning outcomes among Saudi EFL learners. This study is supported by the following hypotheses that seek to illuminate the intricacies of this interaction and its implications for academic achievement within the EFL paradigm:

  • Correlational hypothesis: A significant correlation exists between academic achievement and self-efficacy, use of instructional technology (Blackboard), and English proficiency among Saudi EFL students. This hypothesis seeks to identify whether a relationship exists between the variables without implying that one causes the other.

  • Causal hypothesis: Self-efficacy, the use of instructional technology (Blackboard), and English proficiency have a causal impact on Saudi EFL students’ academic achievement. This hypothesis explores whether changes in self-efficacy, technology use, and English proficiency directly affect academic achievement.

  • Predictive hypothesis: Saudi EFL learners’ academic achievement can be accurately predicted by their levels of self-efficacy, utilization of instructional technology (Blackboard), and English proficiency. This hypothesis tests whether academic achievement can be forecasted based on specified variables.

Literature review

Learning English is made more accessible by incorporating technology such as the Blackboard platform and fostering a sense of self-efficacy as a motivating factor (Makewa et al., 2013). Self-efficacy influences learners’ perceptions of their success in language-learning tasks. Students with a strong sense of self-efficacy are likely to set challenging objectives, exert greater effort, and persevere when facing obstacles (Al-Qadri et al., 2023; Sahan et al., 2023; Teng et al., 2021). Teachers can empower students to take ownership of their language-learning journey and achieve improved results by fostering self-efficacy through effective instructional strategies and support (An et al., 2021). Additionally, integrating technology—as exemplified by platforms such as Blackboard—provides unprecedented opportunities for interactive and compelling language-learning experiences (Al-Oqaily and Salam, 2022). Technology can improve language learning, promote independent learning, and facilitate student communication and collaboration with features like online forums, multimedia resources, and immediate feedback mechanisms (Leba and Temaja, 2023). Adopting technology in language learning creates new avenues for personalized and adaptable learning, allowing students to use their English language skills more effectively in the digital age (Albar, 2023).

Self-efficacy as a motivational factor for language learning

Self-efficacy has emerged as a significant motivator in language learning. This refers to language learners’ confidence in successfully learning and using a new language. Research indicates that high self-efficacy is associated with increased motivation, persistence, and academic achievement in language learning (Bai and Wang, 2023; Honarzad and Rassaei, 2019; Sabti et al., 2019; Sahan et al., 2023).

Studies have demonstrated that self-efficacy influences various facets of language learning, including goal setting, effort, and strategy selection (Alibakhshi et al., 2020; Ismail and Heydarnejad, 2023; Liu et al., 2023). By fostering a sense of self-efficacy, teachers can create a supportive environment that boosts learners’ motivation and promotes successful language learning (Bi et al., 2023). Pan (2020) investigated “technological self-efficacy,” “technology acceptance,” “attitude toward technology-based self-directed learning,” and “learning motivation.” The study found that self-efficacy and technology acceptance positively influenced learners’ attitudes toward technology-based self-directed learning. Learning motivation primarily mediates attitudes toward self-directed learning.

Some studies have explored the relationship between self-efficacy and other motivational variables. For example, Bai and Wang (2023) found that a growth mindset was a more accurate predictor of self-regulated learning among elementary school students than self-efficacy or intrinsic values. An et al. (2021) observed that self-efficacy and enjoyment are associated with technology-based self-regulated learning strategies and English-learning outcomes among university students.

The relationship between self-efficacy and educational outcomes has received considerable attention in the literature. Teng et al. (2021) underscored a positive correlation between self-efficacy, motivation for language learning, and the attainment of English proficiency within distance learning contexts. This highlights the need to nurture metacognitive abilities, motivation, and self-assurance among learners in virtual educational environments (Al-khresheh and Alruwaili, 2024). Similarly, Hennebry-Leung and Xiao (2023) elucidated how learner personality traits and instructional methodologies shape motivation and self-efficacy in language education, providing insights into the development of language-teaching professionals and classroom strategies. Nevertheless, the interplay between self-efficacy and language proficiency is complex, as indicated by divergent research findings. For instance, Wang and Sun (2020) and Rahemi (2007) demonstrated how this relationship can be moderated by a spectrum of factors, such as the educational setting, individual differences among learners, and the particular language abilities being evaluated. These insights introduce an element of variability, suggesting that the conclusions of our study must encapsulate these intricacies. This realization accentuates the imperative for further detailed research to disentangle the multifaceted influence of self-efficacy on language learning.

The relationship between self-efficacy and language-learning outcomes has been investigated in various contexts. For example, Sabti et al. (2019) reported that writing self-efficacy significantly affects writing performance among Iraqi tertiary EFL learners. Abdolrezapour et al. (2023) found that self-efficacy and resilience substantially predict academic motivation in online education, indicating the importance of promoting these factors to improve EFL learning outcomes. Similarly, Sahan et al. (2023) revealed that students’ motivation, perceived competence, self-efficacy, and the amount of a second/foreign language used in the classroom significantly predicted the severity of language difficulties. Self-efficacy was among the most significant predictors.

Overall, these studies have demonstrated the significance of self-efficacy as a factor in language-learning motivation. Teachers and researchers must understand the connections between self-efficacy, other motivational variables, and learning outcomes to develop effective teaching practices and interventions. Teachers can increase motivation and create an optimal learning environment for successful language learning by cultivating learners’ beliefs and fostering their self-efficacy.

Technology integration: blackboard as a language-learning tool

Technology integration plays a crucial role in enhancing language-learning experiences, and the Blackboard platform has garnered considerable attention in recent years (Lin et al., 2017; Lo, 2020). Blackboard—as a language-learning instrument—provides teachers with a flexible platform for developing interactive and engaging language lessons (Al-Oqaily and Salam, 2022; Liaw, 2008). Blackboard’s capabilities, which include multimedia integration, discussion forums, and online evaluations, enable instructors to seamlessly integrate diverse language-learning activities such as listening, speaking, reading, and writing exercises (Motlhaka, 2020). Additionally, it facilitates student collaboration and communication, allowing students to interact with their peers and obtain immediate instructor feedback. Blackboard enables teachers to leverage technology effectively, nurturing a dynamic and immersive language-learning environment through its user-friendly interface and diverse functionalities (Gördeslioğlu and Yüzer, 2019; Kozlov, 2020; Motlhaka, 2020; Poon, 2013).

Several studies have underscored Blackboard’s positive impact on the teaching–learning process, particularly in enhancing student engagement, focus, and motivation, as well as fostering participation, inspiration, and enjoyment (Alzahrani and Alhalafawy, 2023). Nonetheless, recognizing that these benefits are tempered by challenges is essential. Time constraints, limited digital literacy among educators and students, technical issues, resource limitations, entrenched preferences for traditional teaching methods, and apathy toward new educational technologies are hurdles that can impede the successful adoption of Blackboard. These challenges necessitate deliberate strategies and concerted efforts to overcome them effectively (Huang et al., 2021).

Leba and Temaja (2023) emphasized the significance of multimedia technology in language instruction, highlighting various tools and their advantages for creating contextualized English-language materials. However, the study also acknowledges the difficulties in implementing these technologies and advocates authentic strategies to increase English teacher awareness. Regarding online education, most students viewed Blackboard favorably and perceived it as increasing class participation. Blackboard did not increase interaction considerably compared with traditional face-to-face sessions (Albar, 2023). Another study examined the efficacy of Blackboard in enhancing the speaking skills of Saudi EFL students and highlighted its positive impact during the COVID-19 pandemic. It underscored the significance of prior knowledge and experience with online learning and its function in overcoming difficulties in English-speaking skills (Al-Oqaily and Salam, 2022).

Notably, EFL instructors and students generally perceived the Blackboard platform as a tool for developing speaking skills. Female students and instructors with less experience reported higher satisfaction levels. This study highlighted the shift from passive to active learning and the advantages for Saudi women in overcoming cultural barriers (Al Mahmud, 2022; Hamad, 2017). Teachers viewed Blackboard as a valuable tool for distance learning with benefits such as increased student engagement, flexibility, and improved communication. However, technical issues, training requirements, and maintaining student motivation and participation were identified as obstacles (Chen et al., 2020; Han and Ellis, 2019).

Other studies have focused on the obstacles encountered by EFL teachers during the COVID-19 pandemic, such as limited access to technology, training requirements, difficulties in maintaining student engagement and interaction, and the need to adapt assessments to the online environment (Hakim, 2020; Ilyas, 2018). Blackboard’s effectiveness in facilitating online English-language instruction has been emphasized, as has the need for teacher training and support (Al-khreseh, 2021). Almijlad et al., (2022) identified the technological, institutional, and cultural barriers that must be addressed to successfully integrate the Blackboard system into teaching.

The reviewed studies have highlighted the motivators, barriers, and efficacy of multimedia technology and online learning platforms, such as Blackboard, in educational settings. Teachers and students recognize Blackboard as a practical aid for language learning, citing its motivational impact, engagement-enhancing features, and usability. Blackboard facilitates the creation of contextualized materials, promotes active learning, and enhances student communication and collaboration. Despite technical issues and the need for training, lecturers emphasize the value of enhancing student engagement and course delivery flexibility. These findings emphasize the significance of Blackboard as a potent language-learning tool and the need to resolve obstacles and provide support to enhance teaching and learning experiences.

English language proficiency among Saudi EFL students

The English proficiency of Saudi EFL students is a subject of considerable interest. Several studies have aimed to determine the language proficiency levels of Saudi EFL students and the factors influencing their language-learning outcomes (Alharbi, 2015; Ali et al., 2019; Almayez, 2022; Alrabai, 2018; Alrasheedi, 2020). These studies have revealed the strengths and weaknesses pertaining to English language proficiency. Saudi EFL students must improve their listening, speaking, reading, and writing skills. These studies confirm the need for further improvement. It has been determined that cultural and educational background, language-learning strategies, and exposure to English outside of the classroom significantly impact the English language proficiency of Saudi EFL students (Alshammari, 2022; Assulaimani, 2019). These findings contribute to ongoing efforts to improve English-language instruction and address the specific language proficiency requirements of Saudi EFL students.

Several studies have examined the various facets of English-language proficiency among Saudi EFL learners, revealing various obstacles. Al-Oqaily and Salam (2022) confirmed that Saudi EFL students need to develop better speaking skills. Haque et al. (2023) discovered that Saudi EFL learners did not exhibit a precise level of autonomy in their learning, indicating a lower possibility of self-directed language learning. Ali et al. (2019) found that although Saudi EFL students exhibited positive attitudes toward speaking skills and recognized the significance of effective oral communication in English, their oral communication had still not reached the required level. Alrasheedi (2020) identified language apprehension, lack of self-confidence, insufficient exposure to authentic English contexts, and insufficient speaking practice as contributors to Saudi EFL learners’ difficulties in developing their language skills. Ali et al. (2019) found that students’ perceived levels of English proficiency were average. The results revealed a significant positive correlation between perceived English proficiency and attitudes toward English, classroom activities, teacher motivation, and classroom environment. Alrabai (2018) emphasized the need to enhance English-language education in Saudi Arabia, highlighting the significance of addressing particular obstacles to improving language-learning outcomes.

Saleem et al. (2018) discovered a positive correlation between students’ perceived self-efficacy and their English-language proficiency, indicating that students with stronger convictions in their control over the learning process were more likely to attain a higher level of language proficiency. Assulaimani (2019) emphasized the significance of ongoing professional development for teachers and the incorporation of innovative teaching strategies to fulfill the changing requirements of Saudi EFL students. Mitchell and Alfuraih (2017) discussed the government’s efforts to increase English language proficiency in Saudi Arabia, acknowledging the inherent difficulties in implementing effective language-teaching methodologies.

Alharbi (2015) suggested incorporating interactive and communicative activities, providing opportunities for meaningful speaking practice, and employing technology to improve students’ speaking abilities. Alrabai (2017) investigated the independence of Saudi EFL students, emphasizing the need for learner-centered approaches and the growth of independent learning abilities. Alfarwan (2021) examined Saudi EFL learners’ reading strategies—considering gender and proficiency—and emphasized the significance of individual differences and learner characteristics in designing effective reading instruction. Al-Seghayer (2021) reported that Saudi EFL learners favor multiple learning styles, with the visual learning style dominating. Al-khresheh and Al-Ruwaili (2020) analyzed the vocabulary-learning strategies utilized by Saudi EFL learners and provided insights into practical strategies for vocabulary learning, indicating moderate vocabulary awareness. Kaliyadan et al. (2015) highlighted the positive correlation between English-language proficiency and academic performance among Saudi students in a preparatory year program, demonstrating the significance of English proficiency for academic achievement. The possible reasons for the low achievement of Saudi EFL students were explored by Alshammari (2022), who identified issues related to objectives, students, teachers, curricula, evaluations, and practicality. This study highlights the need for relevant, reliable, and practical assistance to improve English language competence. Additionally, it suggests a macro-level understanding of Saudi EFL learners to provide clear-cut recommendations for improving their performance.

In conclusion, the reviewed studies have suggested that Saudi EFL students encounter various obstacles to achieving high levels of English proficiency. The contributors to their low proficiency levels include limited exposure to authentic English contexts, insufficient speaking exercises, language anxiety, and a gap between objectives and classroom practice.

Finally, while some studies have examined self-efficacy as a motivational construct and technology integration, as represented by Blackboard as a language-learning tool, as well as various aspects of English proficiency among Saudi EFL students, a gap exists in our understanding of the relationship between these factors. No study has specifically examined the effect of self-efficacy as a motivational construct or the integration of technology via Blackboard on Saudi EFL students’ English proficiency. To address this gap, in this study, we investigate this connection by developing a relationship model that explores the correlation between self-efficacy, Blackboard integration, and English proficiency and the impact of this relationship on the overall academic achievement of Saudi EFL students. This study aims to contribute to the understanding of the complex relationships between these important variables and provide researchers and teachers with valuable insights into the language-learning and instructional fields.

Theoretical framework

This study builds on a theoretical framework that integrates the tenets of technological pedagogical content knowledge (TPACK) and social cognitive theory (SCT). The integration of this framework is crucial for thoroughly examining the intricate relationship between self-efficacy, the use of Blackboard instructional technology, and English-language proficiency among students enrolled in EFL programs in Saudi Arabia.

Albert Bandura’s SCT offers a comprehensive framework for analyzing the complex phenomenon of learning (Schunk and DiBenedetto, 2020). According to SCT, the interactions among the personal, behavioral, and environmental factors influencing knowledge acquisition are described effectively in Bandura’s triadic reciprocity model (Koutroubas and Galanakis, 2022). An essential element of this framework is the notion of self-efficacy, which is supposed to substantially influence learners’ motivation and subsequent learning behaviors. In this study’s context, SCT functions as a lens through which we can analyze the impact of self-efficacy on academic achievement, explicitly concerning mastery of English.

Furthermore, the TPACK framework offers a more detailed viewpoint on the integration of technology into education (Shafie et al., 2019). It emphasizes the crucial interconnection between technological, pedagogical, and content-related knowledge and contends that a nuanced understanding of how these domains converge is essential to successfully integrate technology into instruction (Santos and Castro, 2021). This study examined the use of Blackboard as an instructional tool from the perspective of TPACK, thereby highlighting the capacity of technological resources to enhance the results of language education.

A strong relationship exists between TPACK and SCT (Dikmen and Demirer, 2022). The symbiotic relationship between TPACK and SCT provides a solid theoretical foundation for the proposed research model, which seeks to clarify the interdependent connections among the pedagogical application of instructional technology, achievement of linguistic proficiency, and psychological construct of self-efficacy. This integrated framework considers the individual components of the educational process as well as the overall effect that results from the strategic synchronization of these components. The purpose of operationalizing the constructs obtained from SCT and TPACK in this study was to evaluate their effectiveness in predicting academic achievement. The theoretical principles of these frameworks have influenced the formulation of research inquiries, thus determining the approach adopted to collect and analyze data. Therefore, this study aims to thoroughly evaluate the proposed structural model, which hypothesizes reciprocal interactions among the identified variables, as Fig. 1 depicts. This conceptualization stems from an extensive review of the theoretical framework and a critical analysis of prior research, which collectively underscores the theoretical connections among these variables. Notably, previous studies have not examined these variables within a unified model—an objective that this study aims to accomplish, thereby contributing a comprehensive perspective to the existing body of knowledge.

Fig. 1
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Hypothetical structural model of reciprocal study variables.

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Research method

As stated above, this study primarily aims to investigate the relationship between self-efficacy, technology integration utilizing the Blackboard management system, and the language-learning outcomes of Saudi EFL students. Remarkably, this study aimed to develop a relationship-based model that describes the direct and indirect impacts of these variables and their primary effects on the overall academic achievement of Saudi EFL students.

Research design

A quantitative correlational design was employed to achieve these objectives. This research design enables the examination of relationships and associations between variables including self-efficacy, Blackboard integration, and English proficiency among Saudi EFL students. This design offers a systematic method for examining how changes in one variable correlate with changes in another, thereby revealing the strength and direction of the relationship (Gravetter & Forzano, 2018). Employing this methodology, the researchers intended to collect quantitative data to shed light on the relationships between these variables.

Participants

This study encompassed a diverse group of 590 university students balanced in sex distribution, comprising 290 male and 300 female subjects. The Arabic-speaking English students were aged between 18 and 28 years, reflecting a range of maturity and academic experience. Universities were deliberately selected using a purposive selection approach for data collection to ensure a varied and relevant dataset.

To select participants, the researchers employed a stratified random sampling strategy—a crucial step to ensure the sample’s representativeness and minimize potential biases. This sampling method was methodically executed, stratifying the sample according to critical demographics, specifically, sex and university education level. This stratification aimed to capture a comprehensive cross-section of the target population, acknowledging and accommodating potential variations in integrating Blackboard, English proficiency, and self-efficacy across these groups.

Random selection from each stratum was instrumental in mitigating the effects of variables that could vary with sex and university level. This careful, strategic approach to sampling not only fortified the validity of the correlations analyzed between the focal variables but also significantly enhanced the generalizability of the study’s findings. Employing this technique aligns with optimal practices in educational research, as suggested by Creswell (2014). A detailed breakdown of the sample characteristics is presented in Table 1, which offers a clear view of the study’s diverse, representative participant base.

Table 1 Characteristics of the sample.
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Table 1 illustrates the demographic composition of the study sample, highlighting the distribution across academic years and sex. The data reveal a balanced representation across all four academic levels, with a notable trend in sex distribution. In the first and second years, male participants were slightly more prevalent, each constituting 16% of the sample, in contrast to 11% and 13% of their female counterparts, respectively. On the contrary, in the third and fourth years, female participants formed a more significant portion of the sample, at 11% and 15%, respectively, compared to 8% and 9% of males. This varied distribution underscores the diversity of the sample, providing a broad spectrum of insights and experiences from different stages of a university’s academic journey.

Instruments

In this study, data were gathered by administering three independent questionnaires to comprehensively evaluate the variables. The initial instrument used in this study was a six-item subscale derived from Gonzales’ (2006) comprehensive questionnaire. This subscale was meticulously selected for its focus on self-efficacy as a motivational construct, which aligned with the study’s objectives to gauge students’ self-efficacy. Notably, the reliability of this scale in its original deployment was robust, as evidenced by a reliability coefficient of 0.892. This figure underscores the scale’s high degree of consistency and reliability, affirming its suitability for accurately measuring self-efficacy in our study context.

The second tool employed in this study was based on Ali et al. (2019) in-depth questionnaire, which assessed Blackboard’s role in facilitating English-language acquisition. This questionnaire included 16 targeted questions to gauge students’ engagement with Blackboard in English-language learning. Of these, nine items investigate intrinsic motivational aspects, while the remaining seven focus on extrinsic motivational factors. The original application of this scale exhibited a notable reliability level, as evidenced by reliability coefficients ranging from 0.75 to 0.82. These coefficients reflect the instrument’s robustness and appropriateness for evaluating the impact of Blackboard on language learning.

The third questionnaire utilized in our study was developed by Makewa et al. (2013) and was specifically designed to evaluate students’ English language proficiency and associated factors. This comprehensive tool encompasses 35 questions divided into three distinct sections. The first section, comprising five questions, focuses on gauging the students’ perceived level of proficiency. The second section, with 10 questions, delves into student-related factors, including attitudes toward language learning and anxiety levels. The final section, the most extensive one with 20 questions, concentrates on teacher-related factors, exploring teacher motivation, classroom activities, available learning resources, and the overall classroom environment. Notably, the reliability coefficients for this scale in its original form varied from 0.72 to 0.86, indicating a high degree of consistency and reliability in measuring the intended variables.

These surveys were merged into a single Google Forms questionnaire. The participants’ ages, sex, GPAs, and university levels were recorded in the demographic section. All questionnaires used a five-point Likert scale, with “strongly agree” and “strongly disagree” being the extremes. The use of questionnaires as a data-collection instrument was justified because of their effectiveness in collecting data from numerous participants within a short period. Moreover, the questionnaires provided standardized, structured data, ensuring that the participants’ variables were consistently measured. Using existing questionnaires ensured that the data collected were accurate because these instruments have been tested in similar studies (De Vaus, 2013).

Study variables

The study examined four variables—namely, English proficiency, Blackboard use, self-efficacy, and students’ overall academic achievement—to construct a comprehensive structural model that elucidates the interrelationships among them. Within this framework, the Blackboard platform and self-efficacy variables were considered independent variables, English proficiency was considered a mediating variable, and students’ overall academic achievement served as the dependent variable. To assess the last variable, the participants were requested to report their grade point averages (GPAs) before completing the questionnaire.

Validation and reliability assessment of study instruments

Face validity assessment

The study instruments underwent a rigorous face validity check to ensure their relevance and clarity. A panel of experts from relevant fields reviewed the instruments, focusing on the clarity of the scale statements and their alignment with the intended dimensions. This process involved iterative feedback from reviewers, which led to the refinement and finalization of the instruments. This thorough review ensured that the instruments were understood and appropriately structured to meet the study objectives.

Construct validity verification

Construct validity of the instruments was confirmed through their application to a pilot sample of 40 students. This step involved calculating the correlation coefficients between individual items and overall scores for their respective dimensions. The results revealed that the correlation coefficients for the self-efficacy scale items ranged from 0.843 to 0.916. For the two-dimensional Blackboard scale, the coefficients ranged from 0.663 to 0.895. The language proficiency scale, which encompassed seven dimensions, demonstrated coefficients between 0.769 and 0.960. These statistically significant correlations at the 0.01 level affirmed a high degree of construct validity, indicating that the instruments accurately measured the constructs they were intended to assess.

Reliability analysis

The reliability of the study instruments was ascertained using Cronbach’s alpha. The reliability coefficients for all dimensions of the study instruments were within the acceptable range, varying from 0.82 to 0.94. The overall reliability coefficients for the first, second, and third scales were 0.93, 0.86, and 0.88, respectively. These coefficients exceeded the minimum acceptable reliability threshold of 0.7, confirming the high reliability of the instruments. Such high reliability indicated that the instruments were consistent and robust for application to the study sample, providing reliable, repeatable measurements.

Data collection and ethical considerations

The study data were gathered through an online survey administered using Google Forms during the first academic semester of 2022–2023. The participants were given explicit directions to complete the questionnaire, which was located at the top of the first page. Ethical concerns were carefully addressed to ensure participant anonymity, informed consent, and voluntary participation. Before beginning data collection, the researchers acquired ethical approval from the appropriate institution.

Data analysis

To avoid missing data, collection was conducted using a form with activated mandatory response settings, ensuring the completeness of the data file. For statistical data analysis, this study employed structural equation modeling (SEM)—a comprehensive model that represents the direct and indirect linear relationships between latent and observable variables. It translates a set of hypothesized cause-and-effect relationships between variables into a statistical model. Path analysis was selected because it aligns with the nature of this study and offers advantages conducive to achieving its aims. The AMOS and SPSS statistical software packages were used for data analysis. For structural equation modeling and path analysis, AMOS was used. Additionally, SPSS was utilized to conduct multiple regression analyses and verify the conditions necessary for SEM, such as sample size, multicollinearity, normality, and extreme values.

The variance inflation factor (VIF) test and tolerance tests for each variable ensured no multicollinearity among the study variables. The criterion used to determine the absence of multicollinearity was that the VIF should not exceed 10 and the tolerance value should be greater than 0.05. Additionally, it was confirmed that the data followed a normal distribution by calculating the skewness coefficient, considering that the data were normally distributed if the skewness value approached zero. Table 2 lists the obtained test results.

Table 2 Results of normality and multicollinearity tests.
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Table 2 indicates that the VIF test values for all variables were below the threshold of 10 and ranged from 0.59 to 0.851. Moreover, the tolerance test values fell within the range of 1.175–1.537, exceeding the critical value of 0.05. These findings provide strong evidence of the absence of multicollinearity among the variables. Additionally, the data in the table confirm that the observed data adhered to a normal distribution, as indicated by skewness coefficients ranging from 0.104 to 0.845, which were within the desired range of values.

Results

To test this study’s first hypothesis, which asserts the existence of statistically significant correlations (at a significance level of α ≤ 0.05) between academic achievement and variables such as self-efficacy, technology use in teaching (Blackboard), and English-language proficiency among Saudi EFL students, Pearson’s correlation coefficient was employed. Table 3 presents the results, which indicate the magnitude and statistical significance of the correlation coefficients. This analysis was employed to ascertain the nature and strength of the relationships between academic achievement and the aforementioned variables.

Table 3 Correlation values between variables.
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Table 3 indicates the presence of significant positive correlation coefficients among the study variables. These coefficients ranged from 0.266 to 0.808, all demonstrating statistical significance at a significance level of α ≤ 0.01. This suggested the existence of direct relationships among the variables, satisfying the initial requirements for predicting and validating the proposed causal model. Consequently, a significant association was found to exist between the dependent and independent variables within the network of significant relationships.

To test the second hypothesis, which posits the existence of causal relationships between academic achievement and variables such as self-efficacy, technology use in teaching (Blackboard), and English-language proficiency among Saudi EFL students, a path analysis using AMOS software was employed. The objective was to examine the fit indices of the path analysis model, which involved verifying the hypotheses by matching the correlation matrices of the variables included in the proposed model. Table 4 presents the fit indices, which provide indicators for the path analysis model, thereby assessing the causal relationships between the independent and dependent variables within the initial model.

Table 4 Fit Indices for path analysis of variable correlations.
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Table 4 provides compelling evidence of congruence between the proposed path analysis model and the empirical data obtained from the study sample. The chi-square statistic was significant (χ2 = 301.84), indicating a satisfactory fit to the observed data. Furthermore, the model’s robustness was confirmed by the fit indices within acceptable thresholds, suggesting that the model appropriately represented the underlying data structure. The comparative fit index (CFI) of 0.973, root mean square error of approximation (RMSEA) of 0.051, and goodness-of-fit index (GFI) of 0.953 were particularly indicative of a robust model fit. The path diagram depicted in Fig. 2 visually interprets these relationships and is solidified by the statistical validation of the fit indices.

Fig. 2
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Final structural model path diagram with fit quality indices.

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Table 5 displays the non-standardized regression coefficients, measurement errors, critical ratios, and significance levels of the study variables.

Table 5 Path analysis effects and significance levels.
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Table 5 lists the following findings:

  • There is a significant positive direct effect of “Blackboard” as an independent variable on “English proficiency” as a mediating variable, indicating that “Blackboard” positively influences “English proficiency” with a magnitude of 0.076.

  • There is a significant positive direct effect of “self-efficacy” as an independent variable and “English proficiency” as a mediating variable, indicating that “self-efficacy” positively influences “English proficiency” with a magnitude of 0.943.

  • There is a significant positive direct effect of “Blackboard” as an independent variable on “achievement” as a dependent variable, indicating that “Blackboard” positively influences “achievement” with a magnitude of 0.336.

  • There is a significant positive direct effect of “self-efficacy” as an independent variable and “achievement” as a dependent variable, indicating that “self-efficacy” positively influences “achievement” with a magnitude of 0.193.

  • There is a significant positive direct effect of “English proficiency” as an independent variable on “achievement” as a dependent variable, indicating that “English proficiency” positively influences “achievement” with a magnitude of 0.821.

After finalizing the selection of the structural model for the relationships between the study variables, a mediation analysis was performed. The objective was to assess whether English proficiency is a mediating factor in the relationship between self-efficacy and achievement and between Blackboard and achievement. Furthermore, the significance and magnitude of the indirect effects between the variables in the model were determined. Table 6 presents the results of the mediation analysis of the structural models.

Table 6 Bootstrapping mediation analysis results for the final structural model.
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Table 6 reveals the significant indirect effects of self-efficacy on achievement mediated by English proficiency. The findings indicate that English proficiency acted as a partial mediator between self-efficacy and achievement. Similarly, the analysis demonstrated the significant indirect effects of Blackboard on achievement, mediated by English proficiency, suggesting that English proficiency served as a partial mediator of the relationship between Blackboard and achievement.

To test the third hypothesis, which states that English proficiency, self-efficacy, and Blackboard use can predict Saudi EFL students’ academic achievement, the researcher employed a multi-way analysis of variance (ANOVA) to assess the validity of the study’s hypothesis. Table 7 provides an overview of the analytical results obtained from this analysis.

Table 7 Multi-way ANOVA results for validating the model and testing the third hypothesis.
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Table 7 exhibits the robustness of the model used to test the third hypothesis. The calculated F-value, which was (1107.676), is highly significant at a significance level of (α ≤ 0.01), indicating the model’s statistical validity. Additionally, Table 7 reveals that the coefficient of determination (R square) for the dependent variable, academic achievement, and the independent variables (English proficiency, self-efficacy, and Blackboard use) is (0.653). This implies that approximately 65% of the variance in academic achievement could be explained by the variables included in the study. The remaining 35% of the variance may have been accounted for by other variables that were not examined in this study. Table 8 presents the results of the multiple regression analysis, indicating the use of achievement as the dependent variable and (English proficiency, self-efficacy, and Blackboard use) as the independent (predictor) variables.

Table 8 Multiple regression analysis for predicting the dependent variable.
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Table 8 provides the estimated regression coefficients for the independent variables under study, predicting the dependent variable, academic achievement. Based on these coefficients, the estimated regression equation, as stated by Keith (2019), was as follows: Achievement = 0.470 + (0.070) × Blackboard use + (0.699) × English proficiency + (0.066) × Self-efficacy.

Discussion

This study’s findings imply that the proposed structural model is the optimally fitting model, consistent with the study data, and indicates goodness-of-fit. The structural model revealed that self-efficacy positively affected both English proficiency and overall academic achievement, suggesting that as levels of self-efficacy increase, English proficiency and overall academic achievement increase proportionally. These results provide important insights into the relationship between self-efficacy, English proficiency, and students’ overall academic achievement. First, the proposed structural model being the optimally fitting model indicates that it represents the underlying relationships between the variables based on the study data and goodness-of-fit indicators. This strengthens the model’s reliability and validity in explaining the investigated phenomenon. Previous studies have acknowledged the importance of such relationships (Honarzad and Rassaei, 2019; Ilyas, 2018; Ismail and Heydarnejad, 2023).

Furthermore, the positive effect of self-efficacy on English proficiency and overall academic achievement demonstrates the significance of students’ confidence in their language learning and academic success. Students are more likely to demonstrate higher levels of English proficiency and attain better academic outcomes as their self-efficacy increases (Abdolrezapour et al., 2023). This finding highlights the importance of cultivating students’ beliefs, motivations, and confidence in their language-learning skills. Additionally, the positive correlation between self-efficacy and English proficiency highlights the importance of addressing the psychological and affective aspects of students’ language instruction. Teachers should implement instructional strategies that promote self-efficacy, including task-based learning, collaborative activities, and authentic language use. Creating a classroom environment that recognizes and celebrates students’ accomplishments can boost their self-efficacy and encourage them to excel in their language-learning journey. These findings are consistent with those of other studies that have confirmed the effect of self-efficacy on language learning (Abdolrezapour et al., 2023; Alibakhshi et al., 2020; Teng et al., 2021). However, research suggests a more complex relationship. For instance, Wang and Sun (2020) and Rahemi (2007) indicated that the impact of self-efficacy on language proficiency may be moderated by factors such as learning environment, individual learner differences, and the specific language skills being assessed. These findings introduce a degree of variability that may not be fully captured in the current study, highlighting the need for further nuanced research in this area.

Considering previous findings, the structural model demonstrates that integrating the Blackboard platform as a pedagogical aid positively affects English proficiency and students’ overall academic achievement. This finding underscores the important role of Blackboard in educational contexts, wherein its use not only elevates English proficiency but also markedly contributes to enhancing overall academic achievement (Motlhaka, 2020). Several factors contribute to Blackboard’s positive impact on English proficiency and academic achievement. Blackboard facilitates interactive, immersive language learning. Students are actively immersed in language practice through multimedia materials, interactive exercises, and virtual simulations, which allow them to hone their skills and get immediate feedback, thereby accelerating the development of language proficiency. Albar (2023), Al-Oqaily and Salam (2022), Leba and Temaja (2023), and Lo (2020) are among the authors that have confirmed the significance of technology integration into language learning, and their findings are consistent with these findings. However, a critical review by Al-khresheh (2021) of the efficacy of Blackboard in language instruction revealed that its effectiveness was contingent on several factors. These included the level of digital literacy among students, quality of instructional design, and degree of teacher engagement with the platform.

Second, Blackboard facilitates student-teacher communication and collaboration. Discussion forums, chat functions, and collaborative tools facilitate language use in authentic contexts. Students enhance their language production, critical thinking, and problem-solving skills by participating in meaningful discussions, exchanging ideas, and collaborating on projects (Al Mahmud, 2022; Kozlov, 2020). It provides various accessible learning materials and resources. Accessibility to e-books, online journals, multimedia resources, and educational websites enables students to investigate diverse subjects and extend their knowledge beyond the classroom. Exposure to authentic and diverse language sources enhances language comprehension, vocabulary acquisition, and overall language proficiency (Hamad, 2017). Additionally, Blackboard provides convenience and adaptability, enabling students to customize their learning experiences. The ability to progress at one’s own pace, revisit materials, and engage in self-directed learning fosters a sense of ownership and motivation, increasing engagement and perseverance in language-learning activities (Chen et al., 2020).

In line with Chen et al. (2020) and Han and Ellis’ (2019) studies, this study corroborates that incorporating the Blackboard into educational frameworks markedly improves English proficiency and overall academic success. This positive association reflects the need in today’s digital era to equip students with the skills to handle the challenges of a rapidly evolving global landscape. Mastery of educational technologies, as evidenced by the proficient utilization of tools such as Blackboard, is becoming an increasingly critical requirement in various academic and professional fields. Using Blackboard, students acquire digital literacy skills, familiarize themselves with online tools, and gain experience navigating virtual environments, thereby enhancing their overall technological competence and adaptability (Al-khreseh, 2021). Blackboard’s ability to provide interactive, communicative, and personalized learning experiences; foster collaboration; facilitate access to diverse learning resources; promote learner autonomy; and equip students with essential digital skills contributes to its positive impact on English proficiency and overall academic achievement. Through these benefits, educators can effectively improve their students’ language skills and contribute to their academic success.

This study not only uncovered notable direct effects of self-efficacy and Blackboard use on academic achievement but also elucidated significant indirect effects. As detailed in Table 6, English proficiency emerges as a critical mediator of these dynamics. For example, the influence of self-efficacy on academic success was partially exerted by enhancing English proficiency. This implies that the benefits of self-efficacy extend beyond direct motivational impacts and foster language competencies crucial for academic success. Similarly, while Blackboard boosts academic performance directly, it also exerts an indirect influence by elevating English proficiency levels. These interconnected pathways highlight the critical role of English proficiency as a conduit linking self-efficacy and digital tool use to educational achievement. Such insights reveal the intricate layers of the educational landscape and demonstrate how various elements interact to shape academic outcomes. This understanding is invaluable for educators and policy designers, as it offers a nuanced perspective for developing more effective and holistic educational strategies. These findings differ slightly from those of other studies, which have consistently indicated direct effects of self-efficacy and Blackboard use on academic achievement. This divergence can be attributed to our study’s unique approach to examining these variables. Unlike most previous studies, which have typically focused on dyadic relationships, such as the connection between self-efficacy and English proficiency (Alibakhshi et al., 2020) or self-efficacy and Blackboard use (Leba and Temaja, 2023), our study delves into a more complex framework. Simultaneous exploration of the interplay among the three key variables uncovered layers of influence, including indirect effects that are not readily apparent in studies with a narrower focus. This comprehensive approach highlights the intricate, multifaceted nature of the factors driving academic achievement, offering a broader perspective than that typically seen in the existing literature.

This study’s findings demonstrate the significance of English proficiency, self-efficacy, and the use of instructional technology (Blackboard) in predicting English-language learners’ academic achievement. The positive relationships identified between these variables highlight educators’ potential to improve students’ academic outcomes by emphasizing the development of English-language skills, fostering self-belief and confidence in their abilities, and effectively integrating technology into instructional practices. By recognizing and addressing these factors, educators can create a supportive, engaging learning environment that empowers students, fosters their development of language proficiency, and ultimately contributes to their overall academic success in English-language learning.

Implications

Several pedagogical implications arise from this study’s findings, supporting the positive relationship between self-efficacy, technology integration (Blackboard), and English proficiency and their impact on Saudi EFL students’ academic achievement. Teachers should foster students’ self-efficacy by setting attainable objectives, offering constructive feedback, encouraging self-reflection, and fostering a supportive classroom environment. Students’ confidence is boosted by scaffolded learning experiences and the promotion of autonomy. Similarly, rewarding accomplishments, fostering peer collaboration, and providing role models contribute to the development of self-efficacy. Second, incorporating technologies such as Blackboard into instructional language practices is crucial. Blackboard enables the sharing of interactive learning materials, communication, collaboration, and personalized feedback, thereby enhancing motivation, language skills, and engagement. Third, by recognizing the connection between English proficiency and academic achievement, educators can design task-based communication activities that promote active participation, authentic language use, and meaningful interactions. Finally, instructors must engage in ongoing professional development to increase their knowledge of effective instructional strategies, technological integration, and motivational approaches. Implementing these implications in the Saudi EFL context will create a technology-rich learning environment that fosters students’ self-efficacy, improves English proficiency, and boosts academic achievement.

Limitations and recommendations

This study has some limitations. The sample size of 590 Saudi EFL students—selected using a random stratified sampling method—is a limitation of this study. Future research should use more extensive, diverse samples to address this limitation and increase the findings’ external validity. Moreover, considering the cultural and contextual factors unique to Saudi Arabia, replicating this study with a larger sample that includes students from various regions and educational institutions within the country would be beneficial. Another limitation is the reliance on self-reporting measures to evaluate variables such as self-efficacy, English proficiency, and technology integration. Future research should include objective measures, observations, and self-reporting measures to mitigate this limitation. This would result in a deeper, more accurate understanding of the relationships among self-efficacy, technological integration, English proficiency, and academic achievement among Saudi EFL students. By increasing the sample size and incorporating objective measures, researchers can obtain more robust, reliable results that contribute to a more thorough understanding of the relationship among these variables in the Saudi EFL context.

Conclusion

In summary, this study further supports previously established findings regarding the relationships among the study variables, as demonstrated by the proposed model. The model effectively elucidates the intricate nature of the associations between academic achievement and English proficiency, Blackboard use, and self-efficacy variables while also considering the direct and indirect effects among these variables. These results underscore the significant role of self-efficacy in fostering and advancing students’ academic achievement and language proficiency. Moreover, the study’s findings highlight the substantial contribution of online learning, exemplified by the use of Blackboard, to stimulating students’ motivation, enhancing their academic performance, and enriching their linguistic skills and competencies. These findings align with the trend in universities toward integrating diverse learning modalities for optimal educational outcomes.