Gender Differences in E-Learning Tool Usage Among University Faculty Members in Saudi Arabia Post-COVID-19

Abstract

This study explored the integration of technology into teaching practices by examining how faculty members at a newly established university in Saudi Arabia utilized the Blackboard learning system. Specifically, it investigated the use of multimedia e-learning tools by male and female faculty members during regular teaching periods following the COVID-19 pandemic. A survey questionnaire was developed using a 5-point Likert scale. The instrument covered demographic information, content creation, assessment methods, utility tools, and factors influencing Blackboard usage. Upon receiving approval, the survey was distributed via email to all faculty members across nine colleges. A total of 198 responses were collected and analyzed using both descriptive and inferential statistical methods. The findings indicated that gender had little to no statistically significant impact on the use of key Blackboard tools—such as content creation features (e.g., files, folders, items), assessment tools (e.g., tests, assignments), and utilities (e.g., virtual classes, email)—at the college level. However, when analyzed at the university level, some tools’ usage showed statistically significant gender differences at the α = 0.05 level. Furthermore, both male and female faculty members cited convenience, flexibility in uploading materials, access to virtual classes, and remote assessment of students as primary factors influencing their e-learning preferences.

1. Introduction

Over recent decades, numerous theoretical perspectives and practical approaches have been developed to study the determinants that predict and explain users’ acceptance and adoption of various technologies in education. In particular, distance learning platforms leverage modern communication technologies and the internet to deliver educational content—such as lectures, discussions, assignments, and assessments—through both synchronous and asynchronous formats. Although e-learning had been explored for several years, its significance surged during the COVID-19 pandemic in 2020. In spite of various resource constraints, it rapidly became a critical mode for conducting lectures and administering examinations. Many universities in Saudi Arabia have adopted online learning, leveraging experience gained during the COVID-19 pandemic. While several studies have focused on the quality of online education and student satisfaction during the pandemic, limited research has addressed faculty satisfaction and usage of various online tools in the post-pandemic period, despite continued plans to offer online courses.

2. Literature Review

Several scholars have explored the integration of e-learning tools in education. Babić [1] examined faculty use of e-learning for communication, convenience, and administration. Davis et al. [2] stressed the importance of internet access, technology, and faculty training for effective distance learning. Yulia [3] highlighted its widespread adoption across various educational institutions, from schools to prestigious universities. Stec et al. [4] categorized online learning into three approaches: enhanced learning—incorporates advanced technologies for interactive instruction; blended learning—combines in-person and online teaching methods; and fully online learning—delivers all coursework via digital platforms. E-learning has expanded into various formats, from single online lessons to full virtual programs. Yusuff Adejare [5] proposed a conceptual framework integrating the technology acceptance model (TAM), innovation diffusion theory (IDT), and the DeLone–McLean model to examine factors influencing e-learning platform usage among students in higher education. Key factors investigated included technology infrastructure support, system quality, and information effectiveness in relation to e-learning systems used for course delivery. The findings indicated that all three factors—technology infrastructure support, system quality, and information effectiveness—significantly impact students’ adoption of e-learning platforms and contribute to improved service quality in higher education institutions. Ronak Soni [6] explored the key tools and techniques shaping modern e-learning, with particular emphasis on learning management systems (LMSs) such as Moodle, mobile learning, AI-powered adaptive platforms, and gamification and immersive technologies like virtual and augmented reality (VR/AR). The study found that platforms like Moodle and mobile learning applications significantly enhance learner engagement. Additionally, AI-driven adaptive systems and gamification techniques contribute to more personalized and effective learning experiences. VR/AR technologies were shown to foster immersive learning environments, while cloud-based LMS solutions offer the scalability required to support institutions of varying sizes. Granić [7] conducted a systematic review to identify the most prominent factors influencing the successful adoption of educational technology. The study provides a concise overview of widely used technology acceptance theories and models in educational research, highlighting the dominant role of the technology acceptance model (TAM) and its various extensions (N = 37), as well as its integration with other frameworks (N = 5). Key predictors of adoption—grouped into user, task and technology, and social aspects—include self-efficacy, subjective norms, perceived enjoyment, facilitating conditions, computer anxiety, system accessibility, and technological complexity. Among the technologies studied, e-learning was the most frequently validated mode of delivery, followed by mobile learning, LMSs, and social media platforms. Al Suwailem [8] highlighted e-learning as an electronic guide, providing resources like discussion boards, online workshops, and tutorials. Wohlfart and Wagner [9] conducted a longitudinal study to examine how teachers’ acceptance and integration of digital tools evolved over time. Using qualitative interviews with 13 secondary school teachers across a two-year period, they identified a cyclical pattern: initial rapid adoption, followed by reflection and skill development, and culminating in varied levels of sustained use or reevaluation. Müller and Leyer [10] applied the reasoned action approach to examine the beliefs and intentions underlying university lecturers’ use of digital learning elements. Through a quantitative survey, lecturers reported both their intentions and actual usage. The study found that intention was significantly influenced by attitude, perceived norms, and perceived behavioral control. However, the researchers identified an intention–behavior gap, noting that only a single effort to familiarize oneself with digital tools had a meaningful effect on actual use. Khong, Celik, Le, and colleagues [11] developed an extended technology acceptance model (TAM) incorporating teachers’ technological pedagogical content knowledge (TPACK) and innovativeness to predict their acceptance of technology for online teaching. The model effectively measured behavioral intention to adopt technology-enabled practices and demonstrated a good fit. The findings highlighted the combined influence of TPACK, perceived usefulness (PU), and innovativeness on teachers’ intention to teach online post-pandemic. Additionally, training and institutional support were identified as key predictors of both TPACK and PU. Means and Neisler [12] concluded that the transition to online university teaching had a significant impact on students, particularly those who reported lower levels of satisfaction with online learning. Schlenz et al. [13] reported favorable findings in their study of German school students, revealing a generally positive attitude toward online learning. Many students expressed a desire to continue incorporating some form of online instruction into their future studies. Jaoua et al. [14] emphasized that students’ distance learning experiences in the Arab world are influenced by environment, culture, resources, technology, and educational background. Similarly, in the Kingdom of Saudi Arabia, Al-Qudah (2021) [15] found that students at Taibah University rated e-learning quality positively (3.897 average) and reported high satisfaction levels (4.128 average). Also, Nasrin Altuwairesh [16] conducted a study examining the perceptions of 241 female students at King Saud University in Saudi Arabia regarding online teaching during the COVID-19 pandemic. The findings revealed that many students found the online learning experience convenient and actively engaged in virtual discussions. However, the study also highlighted several challenges faced by students, including a lack of motivation, reduced opportunities for face-to-face interaction, and various technical difficulties. Asmaa and Najib [17] emphasized its role as a social platform for student–instructor interaction. Ayu [18] noted cost- and time-saving benefits, while Masino [19] found that Blackboard virtual classes enhanced faculty–student communication. However, Ja’ashan [20] identified electronic, administrative, and technical barriers to e-learning adoption at Bisha University. Sahar Alshathry and Mohammed Alojail [21] investigated post-pandemic student satisfaction to assess online learning quality and support universities in improving learning outcomes. The study proposed a model based on the updated information system success model, incorporating system quality, service quality, information quality, student–student interaction, and self-directed learning. Data were collected from 150 undergraduates at King Saud University during the second semester of the 2023–2024 academic year and analyzed using the PLS approach. The findings revealed that among the proposed factors, only self-directed learning had a significant impact on student satisfaction with online learning. In terms of gender, earlier, Shaw and Gant [22] noted that the gender gap in internet technology use was narrowing. However, Cuadrado-García et al. [23] found gender differences among faculty in e-learning adoption, online assessments, and student motivation. Al Suwailem (2018) [8] found no significant gender influence on e-learning adoption in a Saudi university. In Saudi Arabia, Solangi et al. [24] used the technology acceptance model (TAM) to identify training, gender, self-efficacy, compatibility, and facilitating conditions as key factors in e-learning adoption. Crawford et al. [25] reported that 80% of higher education institutions in developing economies partially transitioned to virtual learning during the pandemic, though some struggled to adapt. Post-pandemic, universities continue to integrate online platforms like Moodle, Google Classroom, Zoom, Miro, WhatsApp, Microsoft Teams, and Blackboard. Pei and Wu [26] and Wang et al. [27] highlighted the rise of online learning, while Rasmitadila et al. [28] and Sturm and Quaynor [29] explored its various formats, including discussions, social media engagement, and LMS use. Despite its benefits, online learning faces challenges like network issues and technological limitations, especially in developing regions. However, Hafr Al Batin University has a strong IT infrastructure, ensuring efficient Blackboard implementation. Since most studies focused on e-learning during COVID-19, post-pandemic research remains limited. As a result of the COVID-19 pandemic, the majority of studies on e-learning and online education were conducted during that period, with limited recent research available. In the Saudi context, most existing studies on e-learning tools are general in nature, lacking focus on specific platform features and often overlooking gender as a variable. This current study sought to address these gaps by providing recent insights into faculty usage of key e-learning tools—specifically within the specific customized Blackboard learning management system—for teaching purposes in a geographically remote region of Saudi Arabia. Furthermore, most studies in Saudi Arabia and globally have focused on student satisfaction with e-learning tools, rather than on how faculty members utilize these tools to present teaching materials. We examined both overall usage patterns and the frequency with which various Blackboard components are employed during regular (post-pandemic) teaching periods. Additionally, wey explored the relationship between faculty gender and the adoption of specific e-learning tools, particularly within the context of gender-segregated teaching environments in Saudi universities, where male faculty primarily teach male students and female faculty teach female students.

3. Materials and Methods

This study was conducted in a relatively new university in Saudi Arabia called the University of Hafr Al Batin. It is a public institution established on 3 April 2014 by royal decree from King Abdullah. The university is ambitious to make comprehensive academic transformation that is consistent with the goals of Saudi Vision 2030 and in harmony with the foundations and the country’s declared aims of education, scientific research, and community service. Currently, the university consists of five deanships and nine colleges: pharmacy, applied medical sciences, arts, business administration, computer science and engineering, education, engineering, sciences and supporting studies, and applied college. These colleges are staffed by almost a thousand highly qualified faculty members from both within the Kingdom of Saudi Arabia and a diverse range of countries worldwide. Also, the student population has steadily grown, with over twenty thousand students now enrolled in various diploma, bachelor’s, and increasingly master’s programs. In parallel, the university’s research activities and centers have significantly advanced, contributing to an improved institutional ranking. In addition, the university had adopted e-learning early on, but its implementation accelerated significantly following the onset of the COVID-19 pandemic in 2021 as part of the government’s Saudi Vision 2030. In general, e-learning systems and techniques play a crucial role in enhancing higher education, as noted by many researchers cited in the previous section. This study examined faculty utilization of an important e-learning platform (Blackboard) and its tools. We tested the null hypothesis that gender does not significantly affect the use of content, evaluation, or support utilities (α = 0.05) at either college or university level. The analysis first assessed tool usage at the college level before expanding this university-wide. To achieve the objectives, we applied statistical and inferential analyses to evaluate usage patterns and test hypotheses.

3.1. Blackboard

E-learning represents a modern educational paradigm that emphasizes the integration of information and communication technologies within a unified system. A leading platform that facilitates this integration is Blackboard—a web-based learning management system (LMS) designed to support collaboration between students and faculty. It is essential for uploading lecture notes, presentations, readings, and other teaching materials, making it a core part of course delivery. The system is used by many universities locally and internationally, where it enables users to share files, engage in discussions, complete assignments, and conduct online assessments. In addition to these core functionalities, Blackboard offers a wide range of supplementary features, including reporting, tracking, and administrative tools that enhance its value to educational institutions. As noted by Ababneh et al. [30], Blackboard functions as a multimedia interactive e-learning environment adopted by numerous academic institutions worldwide for both synchronous and asynchronous learning. As illustrated in Figure 1, the platform comprises several essential components, such as real-time collaboration tools for live lectures, content management tools for uploading instructional materials, assignment activities, communication features, and comprehensive examination modules. Technically, Blackboard operates on a client–server architecture. Teaching materials are hosted on a web server and can be accessed via a browser from any internet-connected device. The system’s distance examination tool is particularly robust, offering features such as IP-based access restrictions, time limitations, randomized question delivery, automatic grading, detailed student feedback, and a variety of question formats, including multiple-choice, true/false, short- and long-answer, matching, and calculation-based items. These customizable options contribute to the system’s flexibility and effectiveness in supporting remote education.

3.2. Survey Design

A survey questionnaire was selected as the most appropriate method for data collection since it keeps the identity of the respondents anonymous by sending the questionnaire through university email. A carefully crafted instrument was developed to evaluate faculty usage of various components of the Blackboard learning management system at the University of Hafr Al Batin, specifically tailored to reflect the customized version of the platform used within the institution. The survey was intentionally structured to align with features familiar to faculty members, thereby facilitating accurate and relevant responses. The questionnaire was divided into two main sections. The first section gathered demographic information, including gender, college affiliation, years of teaching experience at the university, academic rank, preferred language of instruction, prior experience with Blackboard, and its intended purpose. The second section focused on four core domains related to teaching and learning: Building Content, Evaluation, Supporting Utilities, and Influencing Factors, each comprising multiple targeted questions. To ensure accessibility and ease of participation, the survey was made available in both Arabic and English and was designed to take approximately 15 minutes to complete. It was distributed to all faculty members via the official faculty group email, with support from the Deanship of Scientific Research, during the first semester of the 2023–2024 academic year. The survey began with demographic questions and then assessed the frequency of Blackboard usage across the first three domains of the second section. Faculty members rated their usage frequency on a 5-point Likert scale ranging from 1 (never) to 5 (always). In the Influencing Factors section, a similar 5-point Likert scale was used, ranging from 1 (strongly disagree) to 5 (strongly agree), to gauge participants’ perceptions regarding the factors that influence their adoption and use of e-learning. This comprehensive approach allowed the researchers to collect both quantitative data on usage patterns and qualitative insights into faculty attitudes toward e-learning integration.

3.3. Study Sample

The population for this study consisted of full-time faculty members of various academic ranks and genders drawn from the nine colleges at the University of Hafr Al Batin. Most faculty members had gained substantial experience with e-learning tools during the COVID-19 pandemic, having been required to conduct lectures and assessments online via the Blackboard platform. Some faculty had also received formal training on the use of Blackboard through sessions conducted by IT professionals from the university’s Department of Information Technology. For the purpose of analysis, a sample of 198 faculty members who voluntarily completed the survey was utilized. Even though a higher number of responses was received from some colleges, this sample included an equal number of male and female respondents (11 each) from every academic college, thereby ensuring balanced gender representation across disciplines. The participants held a range of academic positions, including lecturer, assistant professor, associate professor, and full professor. The sample was also demographically diverse, comprising both Saudi nationals and a substantial number of expatriates from various countries. To encourage honest and thoughtful responses, a statement assuring the confidentiality of participant responses was prominently displayed at the beginning of the survey. Before full distribution, a pilot study with 10 volunteer faculty members was conducted to assess the clarity and effectiveness of the questionnaire and the suitability of the data collection method. Based on their feedback, only minor wording adjustments were made to improve readability and clarity.

3.4. Data Analysis

The reliability of the questionnaire was evaluated using Cronbach’s alpha, which yielded a coefficient of 0.85, indicating a high level of internal consistency among the survey items. Following the data collection phase, responses were analyzed using SPSS v26 statistical software. Descriptive statistical analyses were conducted for each questionnaire item to provide a comprehensive overview of participant responses at the college level. In addition, inferential statistics were applied, including the use of the independent-sample t-test to examine potential gender-based differences in the usage of e-learning tools at the university level. To further explore the factors influencing e-learning adoption, a list of relevant variables was developed based on a review of existing literature and the researchers’ own teaching experience. The average mean score for each influencing factor was calculated to assess its perceived impact. A subsequent t-test analysis was performed to determine whether any statistically significant differences existed between male and female faculty members in relation to these influencing factors.

4. Results

Again, this study tested the null hypothesis that gender does not significantly influence faculty members’ usage of Blackboard’s core components—content, assessment, and general utilities—at a significance level of α = 0.05. The gender variable is particularly relevant within the context of Saudi Arabia, where gender segregation in education remains prevalent. Typically, male faculty members teach male students and female faculty teach female students, with limited exceptions. In select cases, cross-gender instruction is conducted remotely, often facilitated through online platforms such as Blackboard. The analysis is structured in two phases: first, examining usage patterns at the college level, and then expanding to the university level. This two-tiered approach allows for a more nuanced understanding of gender-based differences, if any, in e-learning engagement. The study employed both descriptive and inferential statistical methods to evaluate the stated hypothesis and support the research objectives. The questionnaire explored how faculty members at the University of Hafr Al Batin used Blackboard tools for teaching. Both descriptive and inferential analysis types were followed. The mean scores were used to analyze the frequency of Blackboard feature usage at both college and university levels, revealing patterns in e-learning tool adoption. The inferential analysis used the p-values of a t-test to identify gender-based differences in Blackboard usage at the university level.

4.1. Demographic Data Analysis

The first part of the survey was comprised of four sections, as follows.

• General information: gender (male, female), rank (lecturer, assistant professor, associate professor, full professor), college, language (Arabic, English, bilingual), teaching experience (less than 1 year, 1–5 years, 6–10 years, more than 10 years), Blackboard experience (1–2 years, 2–3 years, 3–4 years, more than 4 years).
• Content: this section contained components that help the faculty members create new files, items, or folders and upload/design multimedia (text, audio, and video) educational content for the students. The respondents had to choose using a scale of never, rarely, sometimes, often, and always.
• Assessment: this part contained items to create evaluation techniques (assignment or tests) and monitor how students were progressing in their learning throughout the course period. Again, the respondents had to choose using a scale of never, rarely, sometimes, often, and always.
• Utilities: this section contained items for communication and interaction (e-mail, discussion, virtual classes, etc.) and interactive tools (website feed, blogs, and social networks) to be used mostly asynchronously, except for the virtual classes tool, which is utilized synchronously.

Table 1. Distribution of respondents: language, rank, teaching years, experience.

Language	Arabic		English		Both
	38		72		88
	19%		36%		44%
Rank	Lecturer	Assistant professor		Associate professor		Professor
	44	94		35		25
	22%	47%		18%		13%
Teaching years of experience	Less than 5	5 to 10		10 to 15		More than 15
	42	46		52		58
	21%	23%		26%		29%
Blackboard years of experience	Less than 1	1 to 3		3 to 4		More than 4
	18	24		46		110
	9%	12%		23%		56%

summarizes the distribution of respondents by gender and academic rank. Of the 198 respondents, 99 were female (50%) and 99 were male (50%), reflecting the university’s division into male and female sections, where female students are primarily taught by female faculty members and male students by male faculty members. Most faculty members used the system in both Arabic and English (44%) or exclusively in English (36%). Only 19% of faculty members used Blackboard solely in Arabic. The academic rank of the respondents was representative of the faculty population in the university. For example, most faculty members hold the assistant professor rank. Specifically, the participants in this study were: 22% lecturers, 47% assistant professors, 18% associate professors, and 13% professors. Also, Table 1 illustrates the distribution of respondents based on their teaching experience at the university level. Out of the total sample of respondents, 22% had less than 5 years of teaching experience, 46% had 5 to 10 years of experience, and the majority, comprising 58% of the sample, had more than 10 years of teaching experience. In addition, Table 1 provides insights into the respondents’ experience with the Blackboard learning platform. It indicates the number of respondents who had used Blackboard before. The table illustrates that most faculty members had been teaching at the university for over five years and gained substantial experience with Blackboard during the COVID-19 period, receiving either self-guided or university-provided training on its main common features. It shows that nearly 60% of respondents had more than 10 years of teaching experience, and over 80% had been using Blackboard for more than a year. Additionally, all faculty members at the university were required to virtually interact with their students during the COVID-19 period. We did not correlate the years of teaching experience or the years of using Blackboard with the level of tool utilization between the two genders, as all faculty members had received some form of training on the Blackboard learning system and were expected to be familiar with its various tools, and most common tools of the system are relatively easy to understand and manipulate.

Table 2. Faculty distribution among the nine colleges.

Stream	Health Stream	Male	%	Female	%
Health	Pharmacy	11	5.56	11	5.56
	Applied medical sciences	11	5.56	11	5.56
Science	Engineering	11	5.56	11	5.56
	Computer science and engineering	11	5.56	11	5.56
	Applied college	11	5.56	11	5.56
	Science	11	5.56	11	5.56
	Business administration	11	5.56	11	5.56
Human	Arts	11	5.56	11	5.56
	Education	11	5.56	11	5.56
Total		99	50	99	50

presents the distribution of faculty survey participants across the university’s nine colleges, which are grouped into three main academic streams: health (pharmacy, applied medical sciences), science (engineering, computer science and engineering, applied college, science, business administration), and humanities (arts, education). Each college contributed 22 respondents—11 males and 11 females—ensuring balanced gender representation. The sample was considered a reasonable reflection of the broader university population. However, the nationality of members was not considered in the analysis, as all faculty members—whether Saudi or non-Saudi—are subject to the same hiring standards, are expected to be comparably proficient with technology, and have equal access to the university’s digital infrastructure. All instructors are required to utilize computer applications and information systems to support their teaching responsibilities. This study specifically examined gender-based differences in the use of these Blackboard components. The institution mandates that all faculty—regardless of gender—use computer applications and the system’s tools for preparing and delivering instruction. In fact, both male and female faculty members actively utilize the Blackboard platform for uploading course content, conducting assessments, and accessing various teaching tools.

4.2. Data Analysis of Utilizing Tools in the Content Category

Survey results revealed that commonly used Blackboard content components—Create File, Create Item, and Create Folder—were utilized frequently by all faculty members, with average ratings near 4 on a 5-point scale. In contrast, less frequently used tools—such as Audio, Image, Video, Web Link, Learning Module, Lesson Plan, Syllabus, Course Link, and Module Page—received average ratings around 2, indicating limited adoption.

Table 3. Mean (1 to 5) of using tools in the Blackboard content category by all respondents (male and female).

Tool/College	Applied College		Applied Medical Sciences		Pharmacy		Science		Computer Science and Engineering		Engineering		Business Administration		Education		Arts		Averages
Create	M	F	M	F	M	F	M	F	M	F	M	F	M	F	M	F	M	F
Item	5	4.9	3.1	3.7	3.6	3.8	3	4.8	4.8	4.9	4.3	4.7	5	4.9	4.3	4.8	4.3	4.2	4.4
File	3.1	4.9	3.7	4.3	3.7	3.9	1.2	5	4.9	4.9	4.6	4.7	4.8	5	4.2	4.7	4.2	4.5	4.3
Folder	1.3	3.2	3.9	5	3.8	4.1	2.2	3.1	5	4.8	4.5	4.7	4.1	3.9	4.1	4	2.7	2.8	3.8
Audio	3	2.2	1.7	3.8	2.3	2.1	2.6	2.2	2.4	2.7	1	1.2	1	1.3	2.1	2	2.2	1.8	2.1
Image	3.3	2.6	1.8	3.6	1.9	1.7	1.9	2.8	2.1	2.7	1.1	1	2.9	3	3.6	1.1	2.7	2.4	2.4
Video	1.9	2.2	1.8	3.5	2.7	2.6	1.8	2.1	2.7	2.4	1.5	1.3	1.1	1	1.9	2.1	1.9	1.8	2.1
web_link	2.3	2.1	1.9	3.3	2.2	2.3	3.3	2.9	3	2.8	1.9	1.8	1.1	1.2	1.9	1.1	1.6	1.7	2.2
learning_module	1.1	2.5	1.8	3.2	2.3	2.5	2.2	2.4	2.4	2.3	1.7	3.4	1.2	1.3	2.1	1.6	2.1	2.1	2.2
lesson_plan	1.2	2.8	2.1	3.8	2.1	2.4	2.5	2.3	2.1	2.8	1.6	1.7	1.1	1	2.1	1.5	2.1	1.9	2.1
Syllabus	2.1	2.9	2.1	3.1	1.7	2.1	2.9	2.8	1.9	2.6	3.1	3.2	1	1.5	2.1	1.4	2	2.1	2.3
course_link	2.2	1.9	2.7	4.1	2.2	2.3	2.2	1.5	1.9	2.4	2.9	2.9	1.5	1.9	1.9	1.2	1.9	2.2	2.3
module_page	2.1	1.5	2.1	3.4	1.9	1.7	2.4	2.1	2.1	1.9	1.3	1.4	1.2	1.1	1.9	1.1	1.7	1.5	1.8
Averages	2.4	2.9	2.4	3.8	2.6	2.7	2.4	2.9	3	3.1	2.5	2.7	2.2	2.3	2.7	2.3	2.5	2.5	2.7

compares mean tool usage between male and female faculty across colleges. At the college level, usage patterns were generally similar across genders. However, some notable differences were observed. For instance, in the College of Science, female faculty reported a much higher usage of the File tool (mean close to 5) compared to male faculty (mean of 1). Similarly, in the College of Applied Sciences, male faculty used the Folder tool and less common tools like Lesson Plan and Learning Module less frequently than female faculty. These variations may reflect differences in instructional delivery; for example, male faculty in applied fields often conduct more hands-on sessions with fewer theoretical lectures. At the university level,

Table 4. Mean values, p-values, and significance levels from t-tests for gender differences in the content category.

Tool (Create)	Mean (Male)	Mean (Female)	p-Value	Statistical Significance
item	4.2	4.3	0.0187	yes
file	3.9	4.2	0.00021	yes
Content folder	3.2	4.1	0.0298	yes
audio	2.01	2.02	0.912	no
image	2.7	2.5	0.887	no
video	2.1	2.2	0.386	no
weblink	2.2	2.3	0.771	no
Learning module	1.95	2.42	0.0411	yes
Lesson plan	1.9	2.4	0.131	no
syllabus	2.2	2.6	0.0988	no
Course link	2.1	2.2	0.705	no
Module page	1.8	1.8	0.861	no

presents the mean usage values and corresponding p-values derived from t-tests for each content component. Statistically significant differences (p < 0.05) were found in the usage of the most common tools—Item, File, and Folder—indicating gender-based variations in how these tools are used. However, most less commonly used tools showed no significant gender differences, suggesting similar usage patterns across both groups. Overall, many components in the content category remain underutilized by faculty of both genders.

4.3. Data Analysis of Utilizing Tools in the Assessment Category

Table 5. Mean (1 to 5) of using tools in the Blackboard assessment category by all respondents (male and female).

Tool/College	Applied College		Applied Medical Sciences		Pharmacy		Science		Computer Science and Engineering		Engineering		Business Administration		Education		Arts		Averages
Create	M	F	M	F	M	F	M	F	M	F	M	F	M	F	M	F	M	F
Test	2.9	2.5	3.1	4.1	2.2	2.9	3.5	4.1	2.9	4.1	3.8	4.1	1.7	3.6	3.3	3.7	3.4	3.5	3.3
Survey	2.1	2.2	1.5	2.1	1.9	2.1	2.9	2.4	2.7	2.8	3.1	3.3	2.9	2.1	2.9	1.3	1.5	2.1	2.4
Assignment	3.1	3.9	3.4	4.0	3.2	3.4	3.5	4.0	3.9	4.2	4.5	4.7	4.8	3.9	3.3	3.5	3.1	4.1	3.9
Course_Task	2.5	2.6	1.6	2.8	2.1	2.8	2.9	2.6	2.8	2.0	2.9	2.4	1.7	1.9	2.5	1.2	1.7	2.2	2.3
Self_and_Peer_Assessment	1.8	1.7	1.7	2.8	1.6	2.5	2.5	2.1	2.0	2.2	1.2	1.5	1.1	1.3	2.7	1.3	1.9	2.0	1.9
Full_grade_center	2.6	2.9	3.9	3.5	3.9	3.1	3.3	3.6	4.1	4.4	4.5	4.6	2.7	3.3	2.8	1.5	3.1	3.9	3.5
Averages	2.5	2.7	2.6	3.3	2.5	2.8	3.1	3.2	3.1	3.3	3.4	3.5	2.5	2.7	3	2.1	2.5	3	2.9

presents the mean usage of assessment tools among male and female faculty members across the university’s nine colleges. Both genders reported frequent use of core assessment tools—Test, Assignment, and Full Grade Center—with mean scores ranging from 3.3 to 3.8. In contrast, tools such as Survey, Course Task, and Self- and Peer Assessment were rarely used, averaging just above 2. Notable gender-based variations in tool usage were observed in specific colleges, such as the College of Applied Medical Sciences, while other colleges, like the College of Computer Science and Engineering, showed minimal to no differences between male and female faculty. At the university level, significant gender differences emerged in the use of commonly utilized assessment tools.

Table 6. Mean and t-test results (p-values and significance levels) for faculty members in the assessment category.

Item	Mean (Male)	Mean (Female)	p-Value	Statistical Significance
Test	3.1	3.6	0.0021	yes
Survey	2.7	2.3	0.262	no
Assignment	3.8	4.2	0.004	yes
Create_Course_Task	2.3	2.5	0.451	no
Create_Self_and_Peer_Assessment	1.8	2.1	0.541	no
Full_grade_center	3.1	2.9	0.552	no

provides detailed mean scores, t-test p-values, and significance levels for six assessment tools. The results confirm statistically significant gender-based disparities in the use of the Test and Assignment tools, while differences in the usage of less commonly used tools—Survey, Course Task, and Self- and Peer Assessment—were minimal and statistically insignificant.

4.4. Data Analysis of Utilizing Tools in the Utilities Category

Table 7. Mean (1 to 5) of using tools in the Blackboard utilities category by all respondents (male and female).

Item/College	Applied College		Applied Medical Sciences		Pharmacy		Science		Computer Science and Engineering		Engineering		Business Administration		Education		Arts		Averages
	M	F	M	F	M	F	M	F	M	F	M	F	M	F	M	F	M	F
Class_Collaborate_Ultra	3.1	3.6	1.9	4.1	3.0	3.9	3.1	3.7	3.2	3.7	4.6	3.5	3.1	3.2	3.2	2.6	1.9	3.1	3.3
Discussion_Boards	3.5	3.3	2.1	3.9	2.9	4.1	3.9	3.2	3.0	4.1	1.9	2.8	2.1	1.3	3.1	2.5	1.9	2.4	3
Announcements	4.7	4.2	2.9	4.6	4.4	4.4	4.2	5	4.3	4.7	4.7	4.3	4.9	4.1	3.3	2.5	4.6	3.9	4.3
Send_Email	2.6	3.1	2.9	3.6	3.2	1.9	1.8	3.8	1.9	2.8	1.8	2.8	2.9	2.9	2.1	2.2	2.1	2.3	2.7
Calendar	2.9	4.1	2.1	2.9	3.7	2.8	1.9	2.9	1.6	2.7	1.4	2.1	2.3	1.8	2.1	1.9	1.8	1.7	2.5
Glossary	2.2	3.1	2.1	2.9	2.2	1.9	2.7	2.8	1.9	2.3	1.4	1.1	1.3	1.2	2.2	1.8	1.6	1.3	2.1
Blogs	2.0	1.9	1.7	2.5	1.6	3.1	2.8	2.4	1.6	1.9	1.1	1	1.2	1.1	2.0	1.7	1.5	1.6	1.9
Journals	2.9	2.0	1.9	2.9	1.8	1.9	2.1	2.9	1.7	1.9	1.1	1.1	1.3	1.2	2.3	1.6	1.5	1.5	1.9
Wikis	2.2	1.3	1.7	2.4	1.7	2.2	2.1	2.5	1.5	1.9	1.1	1	1.2	1.3	1.3	1.1	1.6	1.4	1.7
Groups	2.5	2.0	1.7	2.9	1.7	1.2	2.1	2.4	1.8	2.3	2.2	2.4	1.1	1.3	2.2	2.0	1.9	2.0	2
Averages	2.9	2.9	2.1	3.3	2.7	2.8	2.7	3.2	2.3	2.9	2.2	2.3	2.2	2	2.4	2	2.1	2.2	2.6

displays the mean values of using various tools in the general utilities category among male and female faculty members across different colleges. According to the table, both genders reported frequent usage of the “announcement”, “class_collaborate_ultra”, and “discussion_board” tools, with mean usage scores of 3.5 or higher. Conversely, other tools such as “send_mail”, “calendar”, “glossary”, “blogs”, “journals”, “wikis”, and “groups” were rarely utilized, with mean usage scores hovering around 2. Notably, the mean responses for components in this category varied from one college to another and between the two genders. For example, respondents from the College of Pharmacy reported using the “discussion board” tool much more frequently than those from the College of Arts.

At the university level, the two-tailed t-test results presented in

Table 8. Mean scores and t-test results (p-values and significance levels) for faculty members in the tool category.

Item	Mean (Male)	Mean (Female)	p-Value	Statistical Significance
Class_Collaborate_Ultra	3.1	3.4	0.031	yes
Discussion_Boards	2.9	2.8	0.334	no
Announcements	4.1	4.4	0.903	no
Send_Email	2.7	2.8	0.0467	no
Calendar	2.2	2.8	0.234	no
Glossary	1.9	2.0	0.621	no
Blogs	1.7	1.9	0.176	no
Journals	1.8	2.0	0.432	no
Wikis	1.9	1.5	0.534	no
Groups	2.0	1.9	0.499	no

indicate significant gender-based differences in the usage of most e-learning tools within this category. An exception is the widely used Collaborate Ultra tool, where the p-value (0.0298) suggests no significant difference in usage between genders. This consistency reflects the tool’s essential role in facilitating online communication and delivering virtual lectures. Mean usage values show that both male and female faculty members heavily rely on Collaborate Ultra and Announcements, use discussion boards and email moderately, and make limited use of the remaining tools in this category. This aligns with a common perception at the university that only a few tools—namely Collaborate Ultra and Announcements—are critical for supporting teaching, while other tools are considered supplementary.

4.5. Data Analysis of the Influencing Factors

Identifying the key factors influencing faculty use of e-learning tools across the categories of content, assessment, and general utilities is essential—this formed the second part of the survey.

Table 9. Mean (1 to 5) of responses for each influencing factor by faculty members (male and female).

Influencing Factor/College	Applied College		Applied Medical Sciences		Pharmacy		Science		Computer Science and Engineering		Engineering		Business Administration		Education		Arts		Averages
	M	F	M	F	M	F	M	F	M	F	M	F	M	F	M	F	M	F
Convenience in uploading teaching material	4.3	4.2	4.5	4.7	4.9	4.8	4.4	4.9	4.9	4.2	4.8	4.2	4.2	5	4.6	4.3	4.5	4.3	4.6
Convenience and flexibility in teaching online	4.5	4.2	3.6	4.7	5	4.6	3.7	4.9	3.9	4.4	3.8	3.2	3.9	4.8	4.2	4.5	4.6	4.1	4.3
Convenience in assessing students	4.1	3.7	3.8	4.4	4,2	4.5	3.6	4.8	3.4	3.8	4.0	3.3	4.1	4.2	4.1	4.8	3.9	4.0	4.1
Convenience in communicating with students	4.9	4.2	4.3	4.7	4.1	4.9	4.2	4.3	4.4	4.5	4.5	3.9	4.1	4.3	4.3	4.4	3.9	3.9	4.4
Enthusiasm/personal reasons	2.7	2.3	3.1	3.9	4.1	4.2	4.8	3.1	3.4	4.1	2.7	2.2	2.4	2.2	4.1	5	3.7	3.5	3.5
Positive and good perceptions about e-learning	3.9	3.6	4.0	3.9	4.1	4.8	4.2	4.3	4.2	4.4	3.7	2.9	2.9	3.6	4.3	4.9	4.0	4.1	4
Encouraged/pressured by my faculty’s administration	2.5	2.7	2.6	2.7	3.3	3.1	4.3	2.8	3.1	3.9	3.1	2.2	1.4	1.9	3.6	3.1	3.1	3.2	3
Encouragement by colleagues	2.7	2.7	3.1	4.0	3.1	3.3	2.3	2.9	3.1	3.4	2.6	2.1	1.4	2.1	4.1	3.3	3.4	3.5	3
technical skills/training	2.9	2.8	3.1	3.8	3.1	3.2	3.3	4.6	3.9	4.0	3.1	2.7	4.9	1.8	2.9	3.1	3.2	3.2	3.4
Strengthen my job security	2.1	2.4	2.1	3.4	2.7	2.9	3.6	2.1	3.3	2.5	2.9	2.4	1.7	2.1	3.4	2.9	3.3	3.0	2.8
Receive incentives or stipends	1.8	2.6	1.6	2.3	1.7	1.5	1.7	3.0	2.1	2.2	1.7	1.5	1.6	1.5	2.9	2.5	2.0	2.1	2.1
Receive recognition/reward	2.1	2.0	1.7	2.1	1.5	2.1	1.4	2.9	2.1	2.1	1.5	1.7	1.1	2.1	3.3	2.8	1.9	2.0	2.1
Promotion/job advancement	2.0	2.1	2	2.2	2.3	2.0	2.8	3.4	3.0	2.1	1.5	1.3	1.4	2.0	2.9	1.5	2.6	3.0	2.3
Averages	3.2	3.1	3.1	3.6	3.4	3.6	3.5	3.7	3.5	3.6	3.1	2.6	2.7	2.9	3.8	3.7	3.4	3.4	3.4

presents the mean responses for each factor affecting e-learning tool usage among male and female faculty at the college level. The data show that faculty responses ranged from neutral to strong agreement on the first six factors, including convenience in uploading teaching materials, flexibility in online teaching, ease of student assessment, virtual communication, personal enthusiasm, and positive perceptions of e-learning. The highest mean was recorded for “convenience in uploading teaching material”, while the lowest was for “receiving incentives, stipends, recognition, or rewards”. This is an indication that both male and female faculty are primarily motivated by practical benefits—particularly those that enhance efficiency in teaching and daily tasks. In contrast, factors such as administrative pressure, job security, rewards, or promotion had minimal influence. Across all colleges and both genders, the responses were consistent, suggesting a shared view that convenience and flexibility are the primary drivers of e-learning tool adoption, rather than long-term career incentives.

4.6. University-Level Influencing Factors

Table 10. Mean and t-test results for the influencing factors among all respondents.

Influencing Factor	Mean (Male)	Mean (Female)	p-Value	Statistical Significance
Convenience in uploading teaching material	4.5	4.4	0.69	no
Convenience and flexibility in teaching online	4.1	4.3	0.011	yes
Convenience to assess students	4.0	4.2	0.048	yes
Convenience in communicating with students	4.3	4.1	0.88	no
My enthusiasm or for my own personal reasons	3.6	3.7	0.89	no
Positive and good perceptions about e-learning	3.9	3.8	0.56	no
Encouraged or pressured by my faculty’s administration	3.0	2.9	0.89	no
Encouragement from my faculty colleagues	1.3	0.7	0.41	no
I have adequate technical skills and enough training	3.5	3.1	0.36	no
Strengthen my job security	2.5	2.7	0.71	no
I receive incentives or stipends	1.8	1.9	0.32	no
I receive recognition or reward	1.8	2.1	0.092	no
Help my promotion or job advancement.	2.2	1.9	0.76	no

presents university-level mean responses by gender, t-test p-values, and corresponding significance levels. In most cases, the p-values exceeded the 0.05 threshold, indicating no statistically significant gender differences for 11 of the 13 influencing factors. Overall, faculty members—regardless of gender—tend to use Blackboard tools based on their specific teaching needs. The results show that both male and female faculty primarily rely on the system for uploading teaching materials, conducting assessments, and communicating with students. In contrast, factors such as administrative pressure, incentives, recognition, and job advancement have minimal impact. Notably, “receiving recognition or rewards” had the lowest mean score (approximately 2) for both genders, highlighting its limited influence on e-learning tool usage.

5. Discussion

Descriptive statistical analysis of the survey responses at the college level indicated that faculty members consistently favored a core set of Blackboard tools within each category—content, assessment, and utility—over less commonly used features. Both male and female faculty members showed similar usage patterns for key tools, such as Create File, Create Item, and Create Folder (averaging around 4/5), Test, Assignment, and Full Grade Center (approximately 3.5/5), and Class Collaborate Ultra and Discussion Board (about 3.6/5). These trends were observed across most colleges, with only slight gender-based differences noted in the Applied College. At the same time, there was no evidence of significant gender differences in the use of less commonly used tools, including content tools (e.g., Video, Audio, Web Link), assessment tools (e.g., Survey, Course Task, Self- and Peer Assessment), and utility tools (e.g., Glossary, Calendar, Wikis, Journals). This suggests that variations in tool usage are more likely influenced by individual teaching styles, departmental culture, or specific instructional needs rather than by gender. However, when responses were grouped and analyzed at the university level using inferential statistics, t-test results indicated statistically significant gender-based differences (p < 0.05) in the frequency of using certain tools, including Item, File, Folder, Test, Assignment, and Class Collaborate Ultra. While these differences were slight, they point to the need for a nuanced understanding of tool adoption patterns. Despite these findings, faculty members of both genders consistently rated key factors influencing Blackboard adoption—such as convenience, ease of uploading materials, effectiveness in online teaching, and support for remote assessment—similarly. These shared priorities highlight the importance of practical functionality and underscore a general consensus on the need for standardized teaching and assessment practices within departments. The study concludes that gender alone is not a primary determinant in the usage of e-learning tools. Instead, other variables—such as academic discipline, pedagogical style, or technological comfort—may play a more substantial role. Therefore, the study is limited by its focus on the first 11 male and 11 female faculty respondents to the designed survey questionnaire from each college at the University of Hafr Al Batin during the first semester of 2023–2024. It primarily examined gender differences, excluding other potentially influential factors such as academic rank, teaching experience, and prior training. This purposeful selection bias centered the study on gender, leaving other variables to be explored in future research to better understand other factors influencing faculty engagement with e-learning platforms. Furthermore, even though the Blackboard learning system is uniformly used by all public universities in Saudi Arabia, the results may not necessarily be generalizable to teaching faculty at other universities within or outside Saudi Arabia, as institutional resources, technology, demographics, culture, and curricula may vary across institutions and could impact e-learning tool usage. Based on the findings, it is recommended that institutions offer targeted training sessions or workshops to help faculty integrate a broader range of Blackboard features into their instruction. By supporting faculty in this way, universities can foster greater adoption of e-learning tools, promote innovation in digital pedagogy, and enhance the overall quality of teaching and learning in higher education.

6. Conclusions

The use of Blackboard tools by male and female faculty members is primarily influenced by teaching needs, personal preferences, departmental practices, and technological proficiency. Descriptive analysis shows that both genders actively use core tools—such as content uploads, assessments, and communication features—with only minor differences at the college level. However, inferential analysis at the university level reveals statistically significant gender-based differences in the use of certain tools. These findings highlight the need for the Ministry of Education to support broader research on e-learning implementation and gender-based usage patterns, particularly within Saudi Arabia’s gender-segregated higher-education system.