Building Information Modelling (BIM) Acceptance and Learning Experiences in Undergraduate Construction Education: A Technology Acceptance Model (TAM) Perspective—An Australian Case Study

Abstract

The architecture, engineering, and construction (AEC) industry is experiencing significant digital transformation, creating a critical need to understand how future professionals perceive and accept emerging technologies. This study applies the Technology Acceptance Model (TAM) to investigate undergraduate construction students’ perceptions of Building Information Modelling (BIM) and examines how these factors influence their views on BIM applications. Using an exploratory mixed-methods approach, we analysed 773 responses from students at an Australian university across AEC disciplines, with 607 providing substantive qualitative feedback. Qualitative thematic analysis provided rich contextual understanding of student perspectives, while quantitative analysis revealed pattern frequencies across disciplines. Findings showed that perceived usefulness (PU) (37.7%) and attitude toward using (ATU) (68.4%) dominated student responses, while perceived ease of use (PEOU) (6.9%) received less attention. Productivity benefits (15.3%) and increased accuracy (7.9%) emerged as primary usefulness drivers. Disciplinary differences were significant, with Civil Engineering students emphasising design validation aspects and Construction Management students focusing on project delivery benefits of BIM. Notably, students exhibited sophisticated ambivalence, recognising BIM’s professional value while expressing concerns regarding the steep learning curve, especially when its adoption is coupled with the integration of emerging technologies such as artificial intelligence. This study contributes to the existing knowledge by: (1) documenting the current state of student perceptions in BIM education; and (2) revealing the complex interplay between technological enthusiasm and socio-professional concerns across both educational and industry settings. These findings provide evidence-based guidance for developing BIM curricula that address both socio-technical competencies and student perceptions, helping bridge the gap between educational outcomes and students’ understanding of industry requirements.

1. Introduction

The incorporation of innovative technologies is especially important in the field of education. Learning and teaching environments consist of a wide range of potential users of technology, designed to enhance the processes of knowledge acquisition and dissemination (Granić & Marangunić, 2019) [1]. To address these requirements, universities worldwide have increasingly incorporated Building Information Modelling (BIM) integrated with artificial intelligence (AI) into their curricula, enabling architecture, engineering, and construction (AEC) students to gain essential skills and competencies that align with the evolving needs of the construction industry (Ghosh, Kristen, & Chasey, 2015; Govender et al., 2022) [2,3].

BIM is a method that utilises advanced technology to develop a digital model of a facility, facilitating intelligent information management throughout its entire lifecycle (Alhusban, 2021) [4]. BIM education focuses on providing learners with the expertise to operate BIM software, handle information effectively, and foster collaboration within the construction and design sectors. As the industry increasingly embraces BIM practices, universities have supported its integration into their curriculum by offering both online and in-person BIM courses. These programs aim to prepare students at the undergraduate and graduate levels with the knowledge and skills necessary to meet evolving industry demands.

Numerous initiatives have been undertaken to integrate BIM into AEC programs at the university level. Several studies have also underscored the positive impact of these educational advancements within the BIM domain (Olowa, E., & Lill, 2023) [5]. While the inclusion of BIM courses in university curricula marks a significant step forward, understanding students’ perceptions of BIM’s potential benefits and its application in the construction industry is even more crucial (Goel, 2025) [6]. Students’ feedback and comprehension of BIM’s capabilities play a vital role in shaping their intentions to pursue further BIM courses, enhance their skills for future careers, or achieve advanced proficiency (Abdirad & Dossick, 2016; Goel, 2025) [6,7]. Their perceived benefits of BIM empower educators to refine course content, ensuring alignment with the latest developments in the construction industry.

This study seeks to examine students’ perceptions at an Australian university regarding their BIM coursework and their understanding of BIM’s critical role within both academic and industry contexts. It aims to provide evidence-based recommendations for curriculum development that integrates socio-technical competencies while addressing student perspectives. This approach seeks to bridge the gap between educational outcomes and students’ awareness of evolving industry demands. Despite the strong connection between BIM adoption in academic and industry sectors, few studies have examined how BIM education has evolved to assess changes in students’ skills and perceptions of its potential benefits over time. Consequently, this study aims to address these gaps by employing the TAM framework to investigate students’ evolving understanding of BIM. It emphasises not only the development of technical competencies, but also the cultivation of students’ understanding, acceptance, and readiness to adopt BIM-enabled technologies in their future professional practice.

2. Literature Review

2.1. BIM in the Education Sector

BIM, which has been employed in professional settings since the 1980s, only later found its way into undergraduate studies. Its formal adoption became increasingly prominent within interdisciplinary architecture and engineering programs. Comprehensive reviews of the existing literature reveal a parallel evolution in the maturity of BIM within educational contexts, mirroring its progressive integration and advancement in the construction industry (Nushi & Basha-Jakupi, 2017; Wang, Huang, Zhang, Jin, & Yang, 2020) [8,9]. These sectors are deeply interconnected, as progress in BIM adoption within the industry necessitates corresponding advancements in BIM-related educational curricula and pedagogical approaches. In Australia, BIM uptake is progressing rapidly, with numerous small- and medium-sized companies (SMEs) striving to keep pace with emerging trends and developments (Hosseini et al., 2016) [10]. According to MinterEllison (2025) [11], in 2016, the House of Representatives Standing Committee on Infrastructure, Transport, and Cities recommended that the Australian Government mandate the use of BIM for major infrastructure projects valued at over AUD 50 million in their report, entitled ‘The Smart Information and Communications Technology’.

In the academic sector, the integration of BIM into construction project management education presents a complex interplay of challenges and opportunities, as highlighted in recent studies. A major obstacle is the persistent misalignment between academic curricula and industry demands, whereby graduates frequently exhibit proficiency in BIM software tools, yet lack a deeper understanding of BIM as an integrated, collaborative process (Abu Alieh, Hosseini, Martek, Wu, & Arashpour, 2024) [12]. This disconnect is particularly evident in deficiencies related to information management standards, such as ISO 19650 [13], and in the comprehension of interdisciplinary workflows central to professional practice (Abu Alieh et al., 2024) [12]. Higher education institutions often encounter difficulties implementing robust BIM programs due to fragmented curricular structures, limited faculty expertise, and constrained institutional resources (Papuraj, Izadyar, & Vrcelj, 2025) [14]. On the other hand, several enablers can support more effective BIM education. These include modular curriculum designs that gradually build students’ competencies over time (Papuraj et al., 2025) [14], strong partnerships between academia and industry that provide exposure to real-world practices, and project-based learning approaches that encourage hands-on, applied learning [15].

The use of standardised competency frameworks also offers a promising way to align educational outcomes with the expectations of the workplace. One increasingly recognised strategy is the development of “T-shaped professionals”, graduates who combine deep technical expertise with the ability to collaborate across disciplines. This approach is seen as a key step toward bridging the gap between academic training and industry needs in BIM education (Abu Alieh et al., 2024) [12].

In the Australian context, in the education sector, the integration of BIM into programs at Australian higher education institutions has been progressive, though not without its challenges (Casasayas, Hosseini, Edwards, Shuchi, & Chowdhury, 2021) [16]. The study conducted by Olatunji (2019) [17] examined undergraduate students’ learning experiences in two construction management subjects—quantity measurement and cost estimation—to evaluate their motivation toward BIM education within the Australian context. The findings revealed 29 decision factors, such as access to ongoing support and the mandatory use of specific BIM tools, which contribute to enhancing students’ success in BIM education.

Prior research in the education sector has also proposed innovative approaches to the design and development of BIM curricula, aiming to enhance alignment with evolving industry demands and technological advancements. In 2006, Guidera (2006) [18] implemented BIM applications as part of an integrative method aimed at improving students’ computer modelling skills in the design studio environment. One year later, Techel and Nassar (2007) [19] integrated BIM within a sustainable design framework, emphasising a streamlined approach to design rules and guidelines centred on sustainability. In 2014, Sunil, Päivi, and Janne (2014) [20] introduced the “OpenBIM” concept in the School of Civil Engineering and Building Services (SCEBS) of Metropolia University of Applied Sciences, Finland, to assist educators in identifying the potential advantages of integrating BIM into their current courses while also equipping them with both theoretical insights and practical expertise. More recently, a strategic framework was established by Zaed, Chen, and Bareka (2024) [21] to introduce an innovative approach to improving architectural education. This framework focuses on incorporating professional skills, fostering collaborations, and integrating products and processes while maintaining excellence in design and construction integrity. It underscores the importance of pervasive BIM project delivery, advocating for the comprehensive integration of BIM methodologies into Architecture, Engineering, and Construction (AEC) education.

While these studies provide valuable insights into the benefits of incorporating BIM into curricula to prepare students for market demands, they often lack a detailed exploration of students’ perceptions and attitudes toward applying BIM in their future careers after completing their degrees. According to Goel (2025) [6] (p. 278), “Today’s BIM learners will become tomorrow’s BIM professionals with their first job in the BIM area”. This statement underscores the importance of understanding students’ perspectives on BIM courses, as well as their views on the advantages and limitations of BIM. In other words, it is essential to incorporate students’ ideas into curriculum design. However, there is limited research on students’ opinions regarding BIM’s utility in both academic and industry contexts, as well as their attitudes toward applying BIM in their future careers.

2.2. The Technology Acceptance Model (TAM)

The TAM traces its origins to the Theory of Reasoned Action (TRA). According to TRA, an individual’s behaviour is determined by their intention to perform it, which is influenced by their personal attitudes toward the behaviour and the social norms they perceive (Ajzen, 1980) [22]. Davis (1985) [23] developed the TAM as a framework for understanding the acceptance of computer technology. The TAM is built on two key dimensions: perceived usefulness (PU) and perceived ease of use (PEOU). The TAM framework suggests that PU and PEOU influence the adoption and utilisation of technology. PU refers to the level at which individuals think that the technology will enhance their job performance, while PEOU indicates the extent to which someone feels that operating a specific system would require little effort (Straub, Keil, & Brenner, 1997) [24]. The TAM also proposes that an individual’s PU and PEOU influence their overall attitude toward using (ATU) the technology, shaping either a positive or negative perception of its adoption. The TAM also includes external variables (EVs), which refer to factors or contextual influences, such as organisational support or training, that can affect an individual’s perceptions of the technology and their subsequent adoption decisions (Krouska, Troussas, & Sgouropoulou, 2023) [25]. Behavioural intention to use (BIU) refers to an individual’s readiness to adopt a system or technology. This intention is shaped by their ATU, which is influenced by the system’s perceived usefulness and ease of use.

Extensive research on the TAM underscores its significant influence and widespread recognition in the broader field of technology acceptance, particularly within information systems (ISs) and e-services at organisational and industry levels. However, despite its extensive application in the technology domain, there remains a significant gap in academic studies exploring its use within educational contexts, specifically in AEC programs (Granić & Marangunić, 2019) [1]. In the education sector, a prominent example of the TAM’s application is the study by Scherer, Siddiq, and Tondeur (2019) [26], which investigated the extent to which teachers integrate technology into their teaching practices. This study considered the influence of three external factors: subjective norms, computer self-efficacy, and facilitating conditions. Similarly, Al-Adwan et al. (2023) [27] employed the TAM to analyse the factors influencing higher education students’ adoption of metaverse technology for learning. By collecting 574 questionnaires from private and public university students in Jordan, the study concluded that personal innovativeness in IT had a significant positive impact on self-efficacy, PEOU, and PU. Research has been conducted on the application of the TAM in BIM-based companies. However, a review of the literature reveals a gap in understanding the behavioural constructs that influence students’ intentions to use BIM and their perceptions of its benefits. While some studies have examined BIM adoption in the AEC industry using the TAM framework (Mata, Ancheta, Batucan, & Gonzales, 2024) [28], limited research explores how students’ perceptions of BIM shape their intention to adopt it and their understanding of its significance for both their academic studies and future careers. To bridge this gap, further exploratory research is needed to investigate students’ perceptions of BIM within academic settings. Accordingly, this study adopts a qualitative, exploratory approach to apply the TAM framework to university students.

3. Research Methodology

3.1. Research Design

This study adopts an exploratory sequential mixed-method design within a pragmatic research paradigm to investigate student acceptance of BIM in construction education. In exploratory sequential mixed-methods research, the process begins with collecting and analysing qualitative data, which is then followed by a quantitative phase (Hoseinzadeh, Sharif-Nia, Ashktorab, & Ebadi, 2024) [29]. First, qualitative data collection and analysis was conducted to answer the question: “What are students’ views/comments on BIM and Parametric Design applications in building design and construction?” This aimed to understand students’ perception of BIM usefulness in university courses. The findings from the qualitative data informed the quantitative analysis, enabling the authors to further investigate and quantify the key concepts and nodes that were prominently highlighted by students. Figure 1 depicts the sequential mixed-method design approach adopted in this study. This methodological approach was selected for several reasons. First, this study’s mixed-method approach captures both the breadth of acceptance patterns and the depth of student rationales, representing a particularly well-suited methodology for the construction education context (Rokooei, 2024) [30]. The construction discipline inherently operates at the intersection of technical systems and human processes, requiring research approaches that similarly bridge quantitative precision and qualitative understanding. Traditional quantitative TAM applications, while valuable for identifying statistical relationships, often fail to capture the contextual nuances critical to understanding technology acceptance in domain-specific educational settings like construction. Second, the exploratory dimension allows for the identification of context-specific acceptance factors that may not be fully captured by generalised technology acceptance frameworks. Third, sequential design facilitates an iterative analytical process, which is essential for understanding the multifaceted nature of BIM acceptance. As Jo, Sarah Van de, Hans, and Mieke Van (2016) [31] emphasise, technology acceptance is highly context-dependent, necessitating both a quantitative assessment of acceptance patterns and a qualitative exploration of underlying rationales.

The pragmatic paradigm underpinning this research acknowledges the complex interplay between objective technological affordances and subjective user experiences in educational environments (Venn-Wycherley et al., 2024) [32]. This philosophical stance is particularly appropriate for BIM education research, where successful implementation of BIM in the education sector depends not only on technical considerations, but also on social and pedagogical factors (Abbasnejad, Nepal, Ahankoob, Nasirian, & Drogemuller, 2021; Hu, 2019) [33,34]. Rather than privileging either positivist measurement or constructivist interpretation, the pragmatic approach embraces what Mutch (2009) [35] describe as “methodological eclecticism”, selecting methods that best address the research questions irrespective of philosophical boundaries. Therefore, the research design of this study incorporates analytical triangulation through:

• Frequency analysis of acceptance themes,
• Relational analysis of construct interactions,
• Contextual analysis of representative narratives.

By examining acceptance through multiple analytical lenses, this study responds to Birgonul and Carrasco’s (2021) [36] call for more comprehensive frameworks that reflect the multidimensional nature of construction technology adoption in educational settings.

We selected the TAM over alternatives like the Unified Theory of Acceptance and Use of Technology (UTAUT) or Diffusion of Innovation due to its simplicity and strong validation in educational contexts. Unlike the UTAUT, which emphasises organisational factors, the TAM is well-suited for non-mandated, individual-use settings such as student engagement with educational technology. Its focus on perceived usefulness aligns with how students assess technology’s value for learning. While it has limitations in addressing social and institutional factors, the TAM’s ability to capture both cognitive and affective dimensions (Ping, Na, & Heshan, 2006; Xia, Zhang, & Zhang, 2018) [37,38] made it the most appropriate choice for our exploratory study of student perceptions in construction education.

3.2. Survey Instrument

Data was collected through a structured survey distributed to undergraduate students enrolled in construction-related programs during the 2023 and 2024 academic years. The survey consisted of four primary sections:

• Demographic Information: Students’ disciplinary focus (Construction Management, Civil Engineering, Quantity Surveying, Project Management, Architecture, or Other) and year level.
• Course Information: Whether the student was responding based on experience in a core or elective subject.
• Technology Experience: Previous exposure to and experience with BIM-AI technologies.
• Open-ended Response: The primary qualitative data collection point with the question: “What are your views/comments on BIM, Parametric Design, Digital Twins applications in building design and construction?”

The open-ended format was deliberately chosen to capture rich, unstructured student perspectives without imposing predetermined response categories, allowing for more authentic data regarding their technology acceptance attitudes (Luo, Moore, Franklin, & Crompton, 2019; Miles, 1994) [39,40].

3.3. Sample and Distribution

The survey was distributed online via institutional learning management systems to undergraduate students enrolled in construction-related programs. Participation was voluntary, and the survey link was distributed to about 800 students across the two academic years (2023–2024). Out of 773 surveys returned, only 607 were complete and included substantive responses to the open-ended question, resulting in a 75% response rate and forming the basis of the qualitative analysis. The sample distribution included 449 (58.1%) students from core subjects and 319 (41.3%) from elective subjects, with 5 (0.6%) not specifying course type (Figure 2).

Disciplinary representation included Construction Management (n = 311, 40.2%), Civil Engineering (n = 424, 54.9%), Quantity Surveying (n = 8, 1.0%), Project Management (n = 8, 1.0%), Architecture (n = 5, 0.6%), and Other (n = 14, 1.8%) (Figure 3).

3.4. Data Analysis

3.4.1. Qualitative Content Analysis

Qualitative data from the open-ended survey responses were analysed using thematic content analysis implemented through NVivo 12 Pro software. The analysis followed a hybrid approach incorporating both deductive and inductive elements (Proudfoot, 2023) [41], with the TAM framework providing the initial deductive coding structure, while allowing for emergent themes through inductive coding.

The analysis process consisted of six sequential phases:

• Familiarisation with Data: Initial reading of all responses to gain comprehensive understanding.
• Development of Coding Framework: Establishment of a preliminary coding structure based on TAM constructs.
• Initial Coding: Application of the preliminary framework to a subset of responses.
• Code Refinement: Revision and expansion of coding categories based on initial coding results.
• Comprehensive Coding: Systematic coding of all 607 substantive responses.
• Theme Development and Review: Identification and refinement of patterns and relationships between codes.

3.4.2. Keyword Development for Thematic Analysis

A systematic approach was employed to develop the keyword lexicon for each TAM construct and the associated sub-themes. This process involved three stages:

• Initial Keyword Identification: Based on the established TAM literature (Venkatesh & Bala, 2008) [42], an initial set of keywords was compiled for each construct.
• Contextual Adaptation: These keywords were adapted to the specific context of BIM-AI in construction education by the first two authors. In instances where the authors initially applied different codes, consensus was reached through discussion and clarification of the underlying rationale for each coding decision.
• Keyword Expansion: The initial keyword set was expanded through synonym generation and contextual analysis of a sample of survey responses, identifying domain-specific terminologies and expressions.

The keyword framework outlined in

Table 1. Selected keywords for guiding thematic analysis.

TAM Construct	Sub-Theme	Keywords
Perceived Usefulness	Productivity	efficiency, efficient, faster, quicker, speed, streamline, time-saving, save time, productivity
	Accuracy	accuracy, accurate, precision, precise, error, mistake, clash, detection, quality
	Collaboration	collaboration, collaborate, communicate, communication, share, stakeholder, team, coordinate
	Visualisation	visual, visualise, visualisation, 3D model, see, display, represent
	Cost Reduction	cost, expense, budget, save money, financial, economical
	Safety and Risk	safety, safe, hazard, risk, accident, incident
Perceived Ease of Use	Learning curve	learn, learning, curve, steep, difficult to learn, hard to learn, complex
	User Friendliness	user friendly, user-friendly, intuitive, easy to use, simple, straightforward
	Information Accessibility	access, accessible, availability, available
	Technical Complexity	technical, complicated, complex, sophisticated
Attitude Toward Using	Very Positive	very useful, very helpful, like, love, enjoy, exciting, good, great, excellent, fantastic, amazing, impressive, revolutionary, efficient, effective, benefits
	Moderately Negative	dislike, hate, frustrate, annoy, bad, poor, waste, useless
	Moderately Positive	uncertain, unclear, ambivalent, mixed feelings, undecided, neutral, balanced view, not sure, moderate
	Very Negative	concern, worry, fear, threat, risk, danger, problem, issue, challenge
Behavioural Intention to Use	Future Use	will use, plan to use, intend to use, future, future use
	Career Relevance	career, job, profession, employment, industry standard, professional
External Variables	Resources and Education	education, university, school, course, curriculum, class, teach, learn, student, resource, facility, tool, equipment, infrastructure, training, workshop
	Industry Support and Maturity	industry, trend, standard, practice, common, norm, regulation, organisation, company, firm, business, workplace, support, management, adoption, adopt, implement, implementation, integrate, incorporate

was the basis for structured coding in NVivo, which resulted in 18 sub-themes for the TAM construct. These keyword sets were implemented as search queries and coding references, with each occurrence reviewed in context to ensure appropriate classification.

3.4.3. Analytic Strategy

NVivo 12 Pro facilitated a three-level analysis strategy:

• Frequency Analysis: Quantification of TAM constructs and sub-themes across the dataset, calculating both raw counts and proportional representation.
• Co-occurrence Analysis: Examination of relationships between constructs and sub-themes through matrix coding queries, identifying patterns of conceptual association.
• Contextual Analysis: In-depth examination of representative quotes for each identified theme to understand the nuanced meanings and contextual factors influencing student perceptions.

This multi-level approach allowed for both quantitative assessment of thematic prevalence and qualitative exploration of meaningful patterns within the data, enhancing the validity of findings through methodological triangulation.

4. Analysis and Findings

This section presents the findings from the analysis of student perceptions and acceptance of BIM in construction education. The analysis was conducted through the lens of the TAM model, which provides a theoretical framework for understanding the factors influencing user acceptance and adoption of new technologies. The data comprises 607 responses from students in construction-related disciplines, providing substantive comments on their views regarding BIM applications in education. The TAM framework provides a systematic method for analysing user acceptance through its key constructs: Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Attitude Toward Using (ATU), Behavioural Intention to Use (BIU), and External Variables (EV).

Table 2. The distribution of TAM dimensions and sub-themes across students’ comments.

TAM Construct	Sub-Theme	No. of References	%
Perceived Usefulness (PU)	Productivity	93	15.3%
	Accuracy	48	7.9%
	Collaboration	36	5.9%
	Visualisation	19	3.1%
	Cost Reduction	21	3.5%
	Safety and Risk	12	2.0%
	Total	229	37.7%
Perceived Ease of Use (PEOU)	Learning curve	28	4.6%
	User Friendliness	2	0.3%
	Information Accessibility	8	1.3%
	Technical Complexity	4	0.7%
	Total	42	6.9%
Attitude Toward Using (ATU)	Very Positive	300	49.4%
	Moderately Negative	23	3.8%
	Moderately Positive	71	11.7%
	Very Negative	21	3.5%
	Total	415	68.4%
Behavioural Intention to Use (BIU)	Future Use	118	19.4%
	Career Relevance	5	0.8%
	Total	123	20.3%
External Variables (EV)	Resources and Education	13	2.1%
	Industry Support and Maturity	18	3.0%
	Total	31	5.1%

illustrates how these TAM dimensions are distributed across students’ responses. Our analysis of student responses reveals significant insights into each of these dimensions, which will be discussed in the following sections.

4.1. Perceived Usefulness (PU)

PU emerged as a dominant factor in students’ evaluation of BIM technologies, with 229 (37.7%) comments addressing this construct. Students predominantly recognised six critical utility aspects: productivity enhancements, improved collaboration, visualisation, cost reduction, improved safety, and increased accuracy. However, productivity enhancement (15.3%), improved accuracy (7.9%), and better collaboration (5.9%) emerged as the top three perceived benefits of BIM.

A word frequency analysis was performed to determine the most commonly used words in students’ feedback concerning the PU aspect of the TAM. To improve precision and accommodate different word forms, a “With Stemmed Words” grouping method was utilised. Furthermore, the count of “Display Words” was adjusted to 25 to allow for a wider context for interpretation, with a minimum word length of three letters to filter out irrelevant words. As shown in Figure 4, the word “efficiency” was the most commonly used word identified in the sub-themes coded under the “PU” dimension of the TAM model in students’ comments.

Lexical analysis of PU-related responses identified key terminologies reflecting students’ conceptualisation of BIM’s utility. “Efficiency” emerged as most prominent (4.00%), followed by “construction” (3.35%) and “BIM” (2.52%). The prevalence of improvement (2.18%), design (2.05%), and cost (1.83%) terms illuminate specific domains where students perceive value. Collaboration terminology (1.74%) appeared with equal frequency as usage terms, highlighting students’ socio-technical understanding of BIM’s utility. Table S1 in Supplementary Materials presents a weighted percentage of the top 10 most occurring words concerning the PU dimension. The outcomes of the word frequency query are further examined in the next section by looking into the sub-themes in more detail one by one.

4.1.1. Productivity Benefits

Students consistently identified efficiency and productivity gains as primary benefits of BIM and AI technologies. For instance, one student from the Construction Management discipline noted:

“I believe that BIM and Artificial Intelligence applications will be highly beneficial in construction as it will allow projects to operate more efficiently”.

Another student from the Civil Engineering discipline stated:

“Personally, I believe that BIM, Digital Twins, and AI make construction more efficient”.

A third respondent from the Construction Management discipline observed that:

“Technologies such as BIM can offer tremendous potential to enhance efficiency, reduce costs, and improve the overall quality of construction projects”.

These statements reflect optimism and a strong endorsement of digital and AI-driven innovations in construction, signalling that students view them as essential for the industry’s advancement. This could also suggest a growing awareness of how technology shapes modern construction practices. The time-saving aspect was frequently mentioned by the students as a tangible benefit. One student commented that:

“BIM could help speed up work, ensuring compliance, aid in costing and maintenance”.

Similarly, another student suggested that:

“BIM applications improve efficiency, save time, increase accuracy, and allow more time to be spent on improving other aspects of building and construction”.

4.1.2. Collaboration Enhancement

The collaborative potential of BIM-AI technologies was recognised by students as transformative for project communication and stakeholder engagement; for instance, they commented that:

“BIM revolutionised the industry by allowing stakeholders to create, manage, and visualise detailed 3D models of buildings and infrastructure. This technology facilitates better collaboration among architects, engineers, contractors, and other stakeholders by providing a single source of truth”. (Civil Engineering discipline)

“BIM makes sharing information of design models, a simpler process”. (Construction Management discipline)

“My view on the adoption of BIM technology is a step forward for the construction industry as it enables collaboration between the stakeholders”. (Construction Management discipline)

Other comments by students from the Construction Management discipline, such as, “Providing stakeholders a unique understanding of the project to be delivered”, acknowledged the value of BIM’s role in creating a common visual language across diverse project teams.

4.1.3. Accuracy and Error Reduction

Error reduction was identified as a significant advantage of BIM implementation. Students mentioned that:

“I believe BIM is the way of the future as it eliminates the human element which is often the cause of error, leading to project budget and program overruns”.

“It could help speed up work, ensuring compliance, aid in costing and maintenance. It could also detect design errors and help create effective and usable spaces”.

Students’ perception of BIM’s potential to enhance accuracy in daily construction works aligns with previous industry research showing that early error/clash detection through BIM can significantly reduce costly changes during the construction phase.

4.2. Perceived Ease of Use (PEOU)

The analysis revealed that the ‘PEOU’ dimension was less frequently mentioned by students (43 comments) compared to other TAM constructs, suggesting potential areas for improvement in BIM education. The thematic analysis of students’ responses highlighted ‘the learning curve’ as a key theme. This finding is further supported by the word frequency analysis illustrated in Figure 5, which reveals that the word “learn” was the most commonly used term among the sub-themes categorised under the “PEOU” aspect of the TAM model in students’ feedback.

Analysis of PEOU-related comments revealed “learn” as the dominant term (6.90%), significantly outweighing others and reflecting students’ primary concern with knowledge acquisition. The prominence of “industry” (2.07%) alongside learning terminology suggests students contextualise learning challenges within professional practice rather than as isolated technical hurdles. Table S2 in Supplementary Materials presents a weighted percentage of the top 10 most occurring words concerning the PEOU dimension. Below are some of the students’ insights regarding the challenges of using BIM in both the education and industry sectors.

4.2.1. Learning Curve and Technical Complexity

It was noted that the technical intricacy of BIM tools was viewed as an obstacle to the PEOU dimension. According to the students’ remarks, it requires a significant amount of time for individuals to become proficient in utilising BIM tools. For instance, one student stated that:

“They are very technical and difficult to learn, especially multiple software’s in a semester. However very rewarding to maintain the final product”.

“Great however hard learning curve”.

“They seem to have a difficult learning curve to master however its very interesting”.

“If we learn, understand and apply these technologies we can foster an environment that develops a plethora of nuance solutions to the present and future problems we encounter”.

These insights suggest a balance of optimism and realism as students recognise the effort required to master BIM-AI technologies, but remain motivated by their potential to significantly impact professional practices and problem-solving capabilities. There was a genuine interest among students in digital technologies, as they found them intriguing and potentially transformative, despite the effort required to learn them.

4.2.2. Information Accessibility

Some students acknowledged the benefits of BIM tools in improving information accessibility, which positively impacts their PEOU.

“I believe BIM to be an extremely valuable and informative tool in construction. It allows for easy understanding of a new development and provides information in an accessible format”.

The thematic analysis revealed a low emphasis on the PEOU of BIM. This could stem from several factors. Firstly, digital technologies often have a steep learning curve, requiring time for users to become proficient. Secondly, the relatively lower emphasis on PEOU compared to the usefulness dimension suggests that students prioritise the potential benefits of BIM over the initial challenges of mastering it. Nonetheless, this is an important consideration for universities and educational institutions when designing curricula to ensure that these technologies are effectively integrated into learning.

4.3. Attitude Toward Using (ATU)

Data analysis revealed 415 comments related to the Attitude Toward Using dimension, indicating strong engagement with BIM and AI technology on an affective level. Student attitudes displayed a mix of enthusiasm and concern, often simultaneously.

4.3.1. Very Positive Attitudes

Many students expressed positive attitudes toward BIM technologies, with the majority highlighting BIM’s contributory role in the construction industry due to its PU (

Table 3. Students’ comments regarding their attitudes toward using BIM-AI technologies.

Example of Very Positive Attitudes	Examples of Very Negative Attitudes (Concerns and Ambivalence)
“I think they are great tools which should be capitalised on as particularly with BIM it assists with visualisation of construction projects and can also help with seeing if they are feasible or not”.	“I think the combination of BIM and Artificial intelligence may eventually make a lot of physical workers redundant. Imagine being able to ask a computer to fully design something for you, and then just touch it up to make details more specific. Exciting yet scary times”.
“Would love to explore BIM further and see how it can assist in my field of work”.	“On face value seems to be an incredibly useful tool and one if mastered can help design and construction professionals massively in their areas of work. it does however raise certain ethical questions to the use of artificial intelligence, whether we are aiding the work of humans or making certain professions obsolete”.
“I think BIM is very beneficial and allows to be creative and design complex ideas that was not possible to create in the past”.

). In essence, students perceive BIM as a useful tool for enabling creativity and fostering innovation in design, particularly for complex ideas that were previously unattainable. The desire to explore BIM further suggests a genuine interest in its capabilities and a willingness to integrate these technologies into their future professional work.

4.3.2. Very Negative Attitudes (Concerns and Ambivalence)

While students were generally positive, they also raised concerns, particularly about the potential for job displacement. For instance, some students highlighted the potential for worker redundancy as a result of combining BIM and AI. This ambivalence is a noteworthy finding, as it demonstrates that students acknowledge the transformative potential of BIM and AI technologies while also voicing concerns about their wider impact on the construction industry.

4.4. Behavioural Intention to Use (BI)

Thematic analysis resulted in 123 comments linked to the ‘Behavioural Intention to Use’ dimension, indicating a strong forward-thinking attitude among students regarding BIM adoption and future use. Numerous students articulated clear plans to incorporate these technologies into their future careers:

“Although I don’t see BIM as something I am keen to learn, I do believe it is important for me to understand as I employ other people to use it in the future”.

“These technologies will surely be instrumental to the success of construction in the future. They are happening now, but the implementation will take some time”.

Students often framed BIM as an essential and unavoidable aspect of the future of construction:

“I believe that as Automative and 3D modelling software become more available that it will provide great assistance to project team of all sizes and become more widely spread across all disciplines”.

“I think they are essential for the future of building and construction”.

“Exactly what I would like to aim my learning post-graduation as this is the direction that the construction industry is heading to in the near future”.

These remarks suggest that students largely regard BIM as an anticipated element of their career paths, although some perceive it more as an obligation than with genuine excitement.

4.5. External Variables (EVs)

External variables, such as the availability of resources, education, industry support, and maturity were mentioned in 31 comments. Students demonstrated an awareness of the industry and educational contexts shaping BIM adoption.

4.5.1. The Availability of Resources and Education

Students recognised the availability of resources and training as a key factor influencing the ease of use and usefulness of BIM. For instance, students highlighted the availability of BIM courses and training:

“It will be fascinating to grow forward to this type of future and learning in advance in university will guide us”. (Civil Engineering discipline)

“Very cool software, hope we get to use it in this course a lot”. (Construction Management discipline)

“Therefore, University’s should be teaching students how to use it effectively so that we are not left behind by future generations”. (Civil Engineering discipline)

“However, the introduction of these technologies also requires adapting to new workflows, training personnel to adapt to technological changes”. (Civil Engineering discipline)

“Weigh up the financial feasibility and undertake usability training”. (Civil Engineering discipline)

“These technologies will provide significant benefits, but successful implementation requires careful planning, good data management, skilled employees and integration with existing workflow”. (Civil Engineering discipline)

4.5.2. Industry Support and Maturity

Students also demonstrated the maturity of the construction industry as a significant factor to the adoption of BIM. Here are some examples of students’ comments:

“Highly applicable, Australia is behind the curve in implementing it. I have seen advanced usage in China”.

“I believe BIM is the way of the future as it eliminates the human element which is often the cause of error, leading to project budget and program overruns. Although, I recognise that its industry wide uptake will be no easy feat, with the requirement to challenge the current construction industry culture (resistance to change)”.

These comments provide valuable insights into students’ perceptions of BIM adoption in relation to the construction industry’s maturity. First, students recognise the challenges associated with BIM implementation, particularly the resistance to change deeply shaping the construction industry’s culture. This reflects their awareness of the barriers to innovation and the importance of overcoming them for successful implementation. Second, despite these challenges, students convey confidence in BIM as a transformative technology critical to the future of construction.

Overall, these insights indicate students’ acknowledgment of the significance of supportive organisational and industry environments, as well as robust educational frameworks, in facilitating BIM adoption.

4.6. Disciplinary Perspectives

The PU of BIM varied significantly across disciplinary perspectives, with Construction Management and Civil Engineering students, the two largest groups, comprising 311 and 424 respondents, respectively. Construction Management students tended to emphasise project delivery, stakeholder collaboration, and productivity as the most significant benefits of BIM. For instance, Construction Management students argued that:

“I believe BIM is the way of the future as it eliminates the human element which is often the cause of error, leading to project budget and program overruns”.

“I find they are useful tools to help deliver successful construction projects and further enhance the design and planning of projects”.

Civil Engineering students displayed a greater focus on design capability of BIM, technical validation, and visualisation:

“BIM for civil engineering because it can help design a building and structure to see if it is structurally safe before even going onsite and spending a dollar on materials”.

“Will definitely be important in actualising and designing a constructable building”.

“Computer vision will greatly enhance BIM applications with real time updates and analytics to the shared model”.

These disciplinary differences demonstrate how professional orientation shapes technology perception among students, highlighting opportunities to adapt BIM education to cater to the specific needs and viewpoints of each discipline.

4.7. Technology-Specific Perceptions

Analysis of technology-specific mentions revealed that BIM (128 mentions) and AI (177 mentions) dominated student discussions, while Digital Twins (28 mentions) and Parametric Design (2 mentions) received significantly less attention. This disparity suggests varying levels of familiarity and perceived relevance among emerging construction technologies. Students frequently conceptualised BIM and AI as linked technologies:

“I believe in the near future AI and BIM will be integrated on a small scale at first to help with the design process and clash detection of construction/building projects”.

“I think the combination of BIM and Artificial intelligence may eventually make a lot of physical workers redundant”.

This integration perspective aligns with industry trends toward automated design validation and generative design approaches, suggesting that students are attuned to emerging technological convergences.

4.8. Year Level and Technology Experience

A comparative analysis of student commentary on BIM and AI in construction between 2023 and 2024 reveals a marked shift from theoretical interest to applied understanding. The 2024 cohort demonstrates greater specificity, highlighting practical benefits such as clash detection, collaboration, and cost estimation, whereas 2023 responses were more general and future focused. This progression likely reflects four key drivers: (1) increased industry adoption, offering students more exposure through internships and project-based learning; (2) curriculum improvements emphasising real-world BIM scenarios; (3) broader access to technical learning resources; and (4) the diffusion of innovation as BIM moves from early adopters to early majority in educational contexts. While both cohorts note usability challenges, 2024 students show higher post-training confidence, suggesting growing self-efficacy supported by better software interfaces, improved training methods, peer learning, and standardisation (Table S3 in Supplementary Materials).

5. Discussion

5.1. Student Perceptions of BIM Technologies

Our analysis revealed that students generally hold positive perceptions of BIM technologies (49.4% very positive sentiment), recognising their value for professional practice while acknowledging implementation challenges. This finding aligns with Shelbourn, Macdonald, McCuen, and Lee’s (2017) [43] comparative study of UK and US student perspectives, which similarly found predominantly positive attitudes toward BIM among construction students. However, our research extends this understanding by systematically categorising perceptions according to the TAM construct, revealing that PU (37.7%) and ATU (68.4%) dominate student thinking, while PEOU (6.9%) receives comparatively less attention.

The prominence of productivity benefits (15.3%), enhanced accuracy (7.9%), and collaboration (5.9%) in student responses supports Ghosh et al.’s (2015) [2] identification of coordination as the primary educational benefit of BIM. However, our findings suggest that students’ appreciation of these benefits is more sophisticated than previously documented, frequently connecting these capabilities to broader professional competencies rather than viewing them as isolated technical advantages. As one civil engineering student noted: “BIM provides three-dimensional models of structures that can identify flaws, deficiencies or weaknesses while also providing stakeholders a unique understanding of the project to be delivered”. This perspective reflects what Kocaturk and Kiviniemi (2013) [44] describe as an integrated understanding of BIM that transcends tool-centric conceptualisations.

The limited emphasis on ease of use concerns contrasts with some previous research. For instance, Puolitaival and Forsythe (2016) [45] identified technical complexity as a significant barrier in BIM education, yet our findings suggest that students may accept this complexity as an inherent aspect of professional tools rather than viewing it as a deterrent. This perspective aligns with Blundell’s (2024) [46] conceptualisation of technology learning as a complex, entangled process where learners engaging with digital technologies often embrace complexity when positioned within meaningful professional contexts. Blundell’s (2024) [46] “human-and” perspective, which recognises the influential role of non-human elements such as technologies in learning environments, helps explain why students in our study emphasised usefulness factors over ease of use concerns. They appear to view BIM technologies as integral components of their professional becoming rather than as isolated tools to be mastered.

Zou, Xu, Jin, Painting, and Li’s (2019) [47] finding that students had “different views on challenges compared to industry professionals” complements our identification of “sophisticated ambivalence” among students. While students in both studies recognised BIM’s value, our qualitative approach revealed more specifically how students balance enthusiasm for professional benefits against concerns about learning curves and implementation barriers, providing educators with more actionable insights for curriculum development.

Additionally, technology perception patterns vary across cultural contexts. While our study was conducted in Australia, Shelbourn et al. (2017) [43] revealed significant differences between UK and US student perspectives on BIM education. Their research found US students emphasised technical proficiency and model-building skills, while UK students focused more on industry relevance and software diversity concerns. UK students also expressed more skepticism about collaboration methods taught in university versus industry practices. Similarly, Wang et al. (2020) [9], in their global review, noted that BIM education approaches reflect regional construction industry priorities. These cross-cultural differences underscore the importance of considering local construction practices when developing BIM curricula, as approaches successful in one region may require adaptation for contexts with different technological and collaborative traditions.

5.2. Disciplinary Differences in BIM Acceptance

The significant differences in BIM acceptance patterns between Civil Engineering and Construction Management students represent a notable contribution to existing knowledge. While previous research has acknowledged disciplinary variations in BIM education needs (Casasayas, Hosseini, Edwards, Shuchi, & Chowdhury, 2021; Kocaturk & Kiviniemi, 2013) [16,44], this study quantifies these differences in terms of perception patterns and acceptance factors. Our findings that Civil Engineering students emphasised design validation aspects while Construction Management students focused on project delivery benefits parallels Zou et al.’s (2019) [47] observation that students’ field of study significantly influenced their perceptions of BIM’s usefulness in different applications.

The disciplinary variations in BIM acceptance also echo Kocaturk and Kiviniemi’s (2013) [44] critical observation that current BIM implementations in education are often “disintegrated from the rest of the curriculum and lack any clear strategic and/or pedagogical agenda”. Our analysis reveals profound epistemological differences in how Civil Engineering and Construction Management students conceptualise BIM’s value, reflecting fundamental disciplinary orientations rather than mere preference variations. Civil Engineering students consistently interpreted BIM through the lens of what Schön (2017) [48] describes as technical rationality, a paradigm that emphasises the systematic application of scientific and engineering principles to problem-solving. Their focus on design validation, clash detection, and structural safety reflected a product-oriented perspective, privileging artifact quality and technical precision. This was evident in their use of terms such as “structurally safe”, “constructable building”, and “computer vision… with real-time updates”. Such a perspective aligns with the prevailing pedagogical orientation in engineering education, which Bernstein (2000) [49] identifies as characterised by vertical knowledge structures—hierarchically organised bodies of knowledge where learning progresses through the cumulative integration of abstract concepts and formalised principles. In other words, Civil Engineering students tend to view BIM as a logical extension of their structured learning, using it to reinforce and operationalise the abstract technical knowledge acquired through their coursework. Rather than perceiving BIM as a collaborative or socio-organisational platform, they frame it primarily as a tool for engineering problem-solving focused on improving accuracy, validation, and constructability within well-defined technical parameters. Conversely, Construction Management students exhibited what Bernstein characterises as horizontal knowledge structures—forms of knowledge that are segmented, context-dependent, and centred on experiential or situational understanding rather than cumulative theoretical development. In this context, their engagement with BIM reflects a practical orientation, emphasising how the tool supports workflow coordination, stakeholder management, and process optimisation. Rather than viewing BIM as a platform for abstract problem-solving or technical validation, these students approached it as a means to navigate the contingent realities of project execution, where knowledge is applied dynamically in response to specific challenges and operational needs. Most strikingly, clash detection was referenced nearly four times more frequently by Civil Engineering students than Construction Management students, despite its relevance to both disciplines. This disparity suggests that even when engaging with identical BIM functionalities, disciplinary “epistemic frames” (Shaffer) [50] filter technology perceptions through established professional identities. These distinct cognitive schemas have significant implications for interdisciplinary BIM education, suggesting that effective pedagogies must explicitly bridge these epistemological differences rather than assuming shared conceptual frameworks. Without targeted interventions addressing these divergent knowledge structures, BIM education risks reinforcing disciplinary silos rather than fostering the integrated perspective necessary for effective industry implementation.

5.3. Educational Implications of Students’ Perceptions

Our analysis of student perceptions reveals a pattern with significant implications for BIM education and students’ career readiness. While PU and ATU dominated student responses, PEOU received comparatively limited attention (6.9%). The students’ limited focus on ease of use likely stems from restricted industry exposure and practical experience. This finding is particularly important, as it suggests that current educational approaches may be reproducing rather than addressing industry limitations in BIM implementation.

The specific productivity benefits and collaboration improvements identified by students are consistent with current industry priorities, as outlined by Nassereddine, Hatoum, and Hanna (2022) [51]. However, our qualitative analysis indicates that students predominantly interpret these benefits through a technical lens, with an emphasis on BIM’s visualisation capabilities rather than the broader process transformations necessary to realise its full potential. This technically oriented perspective aligns with the findings of Abu Alieh, Hosseini, Martek, Wu, and Arashpour (2024) [12], who report that although graduates generally demonstrate sufficient proficiency in BIM software, they exhibit notable deficiencies in key process-related competencies, including BIM protocols, collaboration and coordination practices, information workflows, and project completion and handover procedures.

The disciplinary differences observed in our analysis provide additional evidence of the existing gap between educational outcomes and industry expectations. Civil Engineering students primarily emphasised design validation aspects, whereas Construction Management students focused on project delivery benefits. While these discipline-specific perceptions are valid within their respective contexts, they also reflect the siloed approach to BIM education that Casasayas et al. (2021) [16] identified as a barrier to effective implementation across the project lifecycle. Furthermore, Abu Alieh et al. (2024) [12] underscore the importance of understanding BIM as an integrated process aligned with information management standards. This reinforces the concern that discipline-specific framings may hinder the cross-disciplinary collaboration and process integration essential for successful BIM adoption in professional practice.

Our findings thus suggest that while students demonstrate adequate technical understanding of BIM, educational programs should further emphasise process integration, cross-disciplinary collaboration, and socio-organisational dimensions of implementation, areas where both student perceptions and industry practice currently demonstrate limitations. Such an approach aligns with Abu Alieh et al.’s (2024) [12] call for education that moves beyond software competency to develop capabilities in information management standards and collaborative workflows. By strengthening these areas, academic programs can directly influence students’ professional preparedness. Enhanced competencies in these domains are likely to improve career prospects, as students become more attractive to employers seeking BIM-literate graduates capable of contributing to innovation and problem-solving. Additionally, our findings on BIM acceptance and disciplinary differences have significant implications for internship experiences and career trajectories in Construction Management and Civil Engineering programs. The disciplinary epistemological differences we identified, with Civil Engineering students favouring technical rationality and Construction Management students emphasising practical coordination, directly impact how students engage with and benefit from industry experiences. The findings suggest that internship programs should be tailored to build on disciplinary strengths while addressing their limited understanding of other BIM aspects. For Civil Engineering students, internships could emphasise collaborative project experiences that complement their strong technical orientation, while Construction Management students would benefit from internships that strengthen technical validation skills alongside their existing process-oriented perspective. This targeted approach would better prepare students for interdisciplinary BIM implementation in industry settings.

Furthermore, integrating more applied, project-based learning components such as internship placements, real-world BIM simulations, or collaborative studio projects may not only enhance employability, but also correlate with improved academic performance, including higher course pass rates, increased engagement, and stronger alignment between academic training and career trajectories in AEC fields.

To bridge the gap between student perceptions and industry needs, we propose several targeted educational interventions. First, project-based learning across AEC disciplines should be adopted to foster real-world collaboration skills. Second, curricula should integrate industry certifications and standards to build process-oriented competencies. Third, partnerships with industry through guest lectures, site visits, and placements can expose students to practical BIM contexts. Additionally, specialised modules on the socio-organisational aspects of BIM, including case studies and stakeholder simulations, can deepen understanding of implementation challenges. Finally, reflective activities should be used to help students critically consider how BIM shapes professional roles. Together, these interventions promote both technical proficiency and the collaborative, organisational, and reflective skills essential for BIM-integrated practice.

Our findings also have specific implications for curriculum development aligned with established educational and industry frameworks. For Civil Engineering programs, our results suggest that BIM education should be integrated with local or international accreditation boards such as the Accreditation Board for Engineering and Technology (ABET) Criterion 3, particularly those focused on designing within realistic constraints and functioning on multidisciplinary teams (ABET, 2021) [52]. By connecting BIM tools directly to design validation and analysis workflows, educators can leverage the technical orientation already present in student perceptions while expanding collaborative competencies. Additionally, the low emphasis students placed on collaborative aspects of BIM suggests a need to strengthen this area to better align with ABET’s outcome requiring students to “function effectively in teams”. This is particularly important, given that BIM serves as a collaborative platform in industry settings. Strengthening this connection in educational settings would better prepare students for professional practice requirements. For Construction Management programs, our findings suggest that CM students already recognise project delivery benefits, but need greater exposure to technical validation aspects of BIM such as clash detection, design validation, and model-based planning and control.

Recent industry competency frameworks like the UK BIM Framework (UK BIM Alliance, 2018) [53] emphasise process management and information standards alongside technical skills. Our finding that students focus heavily on perceived usefulness, but minimally on ease of use, suggests that curricula should incorporate a more structured framework for technical skill development while maintaining strong connections to professional practice benefits. Implementing spiral curriculum approaches where BIM competencies are revisited with increasing complexity across multiple courses would address the learning curve concerns while reinforcing cross-disciplinary applications.

5.4. Theoretical Implications

The TAM served as the theoretical framework for this study, helping to explore how students perceive, evaluate, and form intentions to adopt BIM technologies in their future professional practice. The TAM provided a useful lens for understanding the challenges of integrating BIM into education and its influence on students’ attitudes and behaviours. Our findings highlight the importance of equipping students with BIM skills to support digital transformation in the construction industry and to promote innovation and efficiency. The results align with several core TAM propositions and contribute to a broader understanding of technology acceptance in construction education. As expected, PU emerged as the most influential factor shaping students’ attitudes, particularly in relation to perceived gains in productivity, collaboration, and accuracy.

The analysis also uncovered complex interrelationships in the TAM that have not been fully addressed in prior education research within the AEC sector. Student responses demonstrated a sophisticated understanding of the socio-technical implications of BIM adoption, recognising both benefits and potential disruptions. The mixed feelings shown by numerous students, who are both enthusiastic about the possible advantages and apprehensive regarding job market effects, indicate that embracing technology in construction education requires more intricate assessments than binary acceptance/rejection decisions. The ambivalence that students express toward AI integration in BIM highlights pressing ethical concerns, particularly around job displacement. For example, one student stated, “I think the combination of BIM and AI may eventually make a lot of physical workers redundant”. This reflects broader anxieties around automation’s impact on the workforce, aligning with the findings by Forcael, Garcés, and Lantada (2023) [54], who identified ethical concerns as an emerging issue in construction education. These perspectives highlight the importance of addressing not only technical skills, but also the socio-ethical implications of digital transformation. Rather than viewing displacement as inevitable, education programs should promote ethical technology stewardship (Stahl, 2021) [55], encouraging students to engage critically with how AI reshapes professional roles and responsibilities. Preparing students to navigate these ethical dimensions is essential for responsible industry leadership.

6. Conclusions

This study aimed to investigate construction students’ perceptions and acceptance of BIM through the lens of the TAM model. Using an exploratory mixed-methods approach, we analysed qualitative responses from undergraduate students across multiple construction disciplines to understand how they conceptualise and evaluate BIM within their educational experiences. This analysis of student perceptions revealed generally positive attitudes toward BIM technologies within construction education, with strong recognition of usefulness benefits across productivity, collaboration, and accuracy dimensions. Students demonstrate a sophisticated awareness of both potential benefits and implementation challenges, including concerns about the learning curve and industry adoption barriers. The findings support the TAM’s emphasis on PU as a primary acceptance driver, while extending understanding through the identification of disciplinary differences and the complex ambivalence expressed by many students. Disciplinary differences emerged, with Civil Engineering students focusing on design validation aspects and Construction Management students emphasising project delivery benefits. These discipline-specific perceptions reflect a broader tendency among graduates to possess software skills while lacking cross-disciplinary competencies in BIM protocols, coordination, and information workflows—competencies that employers increasingly require. For educators, these insights suggest opportunities to enhance BIM curricula through discipline-specific applications, structured skill development, and engagement with the broader socio-technical implications of digital construction technologies. This study has several limitations that should be acknowledged. One limitation of this study is the uneven distribution of survey responses across academic disciplines, with a notably larger proportion of participants from Construction Management and Civil Engineering compared to other fields. This disparity may influence the generalisability of quantitative findings, especially when examining differences across disciplines. Nevertheless, the qualitative aspect of this study benefits from the inclusion of diverse perspectives, enabling a more comprehensive exploration of experiences. Although the responses may not be statistically representative, they enhance the thematic analysis and offer valuable contextual insights. Another limitation is that the research was conducted within a single Australian university at the undergraduate level, and caution should be taken when generalising findings to different educational systems, cultural contexts, and student populations. The cross-sectional nature of the data provides only a snapshot of perceptions at a particular point in time, missing potential longitudinal developments. While the TAM offered a structured analytical framework, it may not capture all dimensions of technology acceptance specific to construction education. Future research should extend investigations to multiple institutions across different countries to enable cross-cultural comparisons, conduct longitudinal studies tracking how perceptions evolve from education into professional practice, and compare undergraduate and postgraduate programs to reveal how prior experience influences technology acceptance. This study did not directly evaluate academic outcomes or professional milestones, such as course grades, internship success, or job placement. As a result, the findings are limited to students’ perceptions of BIM’s usefulness and do not establish a causal link between these perceptions and tangible performance indicators. Future longitudinal research is needed to explore how perceptions translate into academic or career achievements over time. In terms of research method, the qualitative component of this study was intentionally narrow in scope, focusing on perception-based data. These limitations are acknowledged as areas for future expansion to strengthen the generalisability and analytical depth of the findings. While our study offers descriptive insights into group-level differences across disciplines and year levels, it is important to note that the observed differences should be interpreted with caution, as they may not reflect statistically significant trends. Future research could expand on these comparisons by employing inferential statistical analyses to assess the significance of observed differences. The qualitative phase of this study relied on responses to a single open-ended survey item. While this approach generated a considerable volume of data, it inherently limits the variety of insights typically associated with more intensive qualitative methods such as interviews or focus groups. Future studies may benefit from incorporating more exploratory qualitative research approaches to capture more nuanced perspectives on students’ experiences with BIM. Additionally, further research should explore how educational programs can better develop process-oriented competencies while addressing the socio-organisational factors that currently limit BIM’s transformative potential in both educational and industry contexts.