The development of a competency framework for architectural engineering graduates: Perspectives by the construction industry in Indonesia

THE DEVELOPMENT OF A COMPETENCY FRAMEWORK FOR ARCHITECTURAL ENGINEERING GRADUATES: PERSPECTIVES BY THE CONSTRUCTION INDUSTRY IN INDONESIA

Rihab Wit Daryono1* , Nur Hidayat2 , Muhammad Nurtanto3 , Athok Fu’adi4

1Department of Islamic Education, Ponorogo State Islamic Institute (Indonesia)

2Department of Civil Engineering and Planning Education, Yogyakarta State University (Indonesia)

3Department of Mechanical Engineering, Jakarta State Polytechnic (Indonesia)

4Islamic Education Management, Ponorogo State Islamic Institute (Indonesia)

Received October 2022

Accepted September 2023

Abstract

The discrepancy between competence and real work in engineering graduates can be resolved with cooperation by the construction industry. Therefore, it is necessary to determine the appropriate and required architectural engineering competencies with the current demands and conditions of the construction industry. So, this study aims to analyze the determinants of competence and test the competency development model for architectural engineering graduates according to the needs of the construction industry. The research sample method is non-probability sampling using purposive sampling. The research sample consisted of 240 practitioners and trainers from 40 construction industry companies. The PLS-SEM technique was used to test the measurement and structural models (3 dimensions, 8 elements, 47 constructs/indicators, and 9 hypotheses). The competence of architecture graduates is determined by the dominant factor, namely Utilities and Building Construction (UBC1 & UBC2, λ = 89.90%), and Building Estimation and Costing (BEC7, λ = 73.30%) is the lowest factor. The ability of the structural model to explain architectural competency measurements is 36.20% in the moderate category. The predictive relevance value (Q2) explains 47.5% to 56.0% of the phenomena predicted in the field and explains the level of strength of the observed value in the structural model. Furthermore, 9 hypotheses from 8 dimensions have a positive and significant effect. The results of this study can be a recommendation for schools in the competency implementation model, and efforts to improve graduates’ abilities and skills so that they can be absorbed by the construction industry and reduce unemployment.

 

Keywords – Architectural engineering, Competency, Construction industry, Students’ graduates, Vocational education.

To cite this article:

Daryono, R.W., Hidayat, N., Nurtanto, M., & Fu’adi, A. (2024). The development of a competency framework for architectural engineering graduates: Perspectives by the construction industry in Indonesia. Journal of Technology and Science Education, 14(2), 274-290. https://doi.org/10.3926/jotse.1986

 

    1. 1. Introduction

Vocational Education (VE) has an important role in preparing a workforce that is required to be able to follow the trend of competency development needed by the industrial world (Olazaran, Albizu, Otero & Lavía, 2019; Perusso & Baaken, 2020). The VE has the main mission to produce workers who have professional skills according to the demands of work competencies and have a good attitude to work (Beicht & Walden, 2019; Setyadi, Triyono & Daryono, 2021). In addition, VE graduates can continue to higher education and are expected to create jobs as independent entrepreneurs (Supriyadi, Indro, Priyanto & Surwi, 2020). The reality on the ground shows that the current existence of VE is considered to be lacking in preparing graduates as ready to work (Beicht & Walden, 2019; Draaisma, Meijers & Kuijpers, 2018; Nurtanto, Arifin, Sofyan, Warju & Nurhaji, 2020; Santoso, Sukardi, Prayitno, Widodo & Daryono, 2022; Setyadi et al., 2021). Improving the quality and competitiveness of resources for VE graduates can be promoted the revitalization of vocational high schools. Operationally, the revitalization of education at VE is realized through: first, increasing collaboration between VE and industry (Kesai, Soegiarso, Hardjomuljadi, Setiawan, Abdullah & Napitupulu, 2018; Olazaran et al., 2019). Second, the involvement and use of industry as a place for internships, work practices, and places to learn the management of the world of work (Ćudić, Alešnik & Hazemali, 2022; Perusso & Baaken, 2020). Third, the alignment of the VE curriculum, by the applied dual system model, both in determining work practice activities and learning through the teaching factory.

According to the results of a national labor force survey conducted by the Central Statistics Agency in Indonesia, in February 2021 the unemployment rate for VE was the highest among other education levels at 7.42%, when compared to August 2020, it increased by 0.16% points. The Central Statistics Agency in Indonesia 2021 revealed that the result data on the unemployment rate for VE graduates was still the highest compared to graduates of other education levels at 11.13%. Meanwhile, the average unemployment rate for several countries in 2021 shows that the unemployment rate in Indonesia is 5.90%, ranking 16th out of 32 countries. This fact shows that the role of vocational schools as educational institutions makes graduates unable to work according to their field of expertise. Thus, this fact indicates that there is a gap between the competencies of VE graduates and industry needs (Daryono, Yolando, Jaedun & Hidayat, 2020; Rosantono, Wijanarka, Daryono & Nurtanto, 2021).

To create the competency alignment between architectural engineering graduates, it is necessary to involve stakeholders and experts in the field of construction in planning and designing graduate competencies (Daryono et al., 2020; Hariyanto, Daryono, Hidayat, Prayitno & Nurtanto, 2022). In addition to the problem of limited employment opportunities due to the country’s economic growth that has not met expectations, the high unemployment rate indicates a mismatch between supply and demand. Both are related to the quality and relevance of competence in the field of expertise between the workforce who graduated from VE and the needs of the industrial world (Ćudić et al., 2022; Kesai et al., 2018). The competency gap between what is reflected in graduates and the competency qualifications required by the industrial world can be reduced by aligning competencies and their relevance according to current needs according industry demands (Okolie, Nwajiuba, Binuomote, Osuji, Onajite & Igwe, 2020; Olazaran et al., 2019).

The perspective of construction industry practitioners as users of architectural engineering graduates is that graduates must have professionalism in work, and they must have competencies and skills that are in accordance with industry needs (Celadyn, 2020; Hariyanto et al., 2022; Taraszkiewicz, 2021). The demand of the industry is not an easy job because it requires good cooperation between schools and industry regarding the development of competencies taught in schools (Daryono, Rochmadi & Hidayat, 2021). This effort has been made by the Indonesian government and schools in compiling a curriculum that involves stakeholders, academics and construction industry experts (Surya & Mulyanti, 2020). The role of stakeholders is the main key in determining and implementing what competencies are taught in schools according to industry demands.

This data also reveals that to enter the world of work, VE graduates still face many challenges. According to (Daryono et al., 2020; Surya & Mulyanti, 2020), there are at least two challenges faced by VE graduates to enter the workforce. First, the curriculum and architectural engineering competencies are not relevant to the competencies demanded in the current construction industry, so the graduate competencies cannot meet the requirements according to industry needs. Second, is the lack of educational facilities and infrastructure at VE in vocational practice learning (Draaisma et al., 2018; Okolie et al., 2020; Olazaran et al., 2019). In addition, schools also need to better direct their graduates to become entrepreneurs, so that it can be one way out to reduce the unemployment rate of VE graduates. So the process of entrepreneurship development and business incubation for students and graduates of VE is very much needed.

The discrepancy between competence and actual work in architectural engineering graduates can be resolved by cooperation and retraining by the construction industry. However, it is rare for the industry to be willing to carry it out because training requires manpower, time, space, and costs so it is not profitable for the company. So, it is important to research architectural engineering competence against the demands and needs of the construction industry. Therefore, this study aims to analyze the determinants of competence and test the competency development model for architectural engineering graduates according to the needs of the construction industry. The results of the research will become input for the development of curriculum and competencies in the architectural engineering department at VE. So that it can increase the competence of graduates and the absorption of VE graduates in the construction service industry. The results of this study can become recommendations for schools in the competency implementation model, and efforts to increase the capabilities and skills of graduates so that they can be absorbed by the construction industry and reduce unemployment.

2. Literature Review

2.1. Basic Fields of Expertise (C1)

The basic fields of expertise subjects are binding substantive subjects that function as the main focus of the vocational program. In the architectural engineering department, competence is divided into several competency areas, namely: Basics and Technical Drawing (BTD), Building Construction Basics (BCB), Engineering Mechanics Statics (EMS), and Land Measurement Techniques (LMT). Basics and Technical Drawing (BTD) is one of the skill competencies that equip students with knowledge and skills in terms of drawing the basics of architectural buildings which includes: drawing pictures of plane shapes, pieces of a building, 2D and 3D projections, and introduction BIM software. Building Construction Basics (BCB) is a skill competency that equips students with the skills to implement and plan materials for a building, including woodwork, concrete, steel, soil, etc. (Li, Zhao & Zhou, 2019; Simpson & Bester, 2017; Taraszkiewicz, 2021). Engineering Mechanics Statics (EMS) is a skill competency that equips students with the skills to analyze and calculate the balance of forces, beams, moments, and other structural elements (Hariyanto et al., 2022; McCrum, 2017). Land Measurement Techniques (LMT) is a competency skill that equips students with field survey skills and tools such as theodolite and spirit level, performance measurement techniques, and staking out and making the results of field survey measurements (Daryono et al., 2020; Hariyanto et al., 2022).

2.2. Basic Skills Program (C2)

The basic skills program subjects are specific vocational content within the scope of skills competency. In the architectural engineering department, competence is divided into several areas of competence, namely: Building Estimation and Costing (BEC), Road and Bridge Construction (RBC), and Utilities and Building Construction (UBC). Building Estimation and Costing (BEC) is a competency skill that equips students with the skills to analyze the calculation of the volume of work in a building, present specifications for building construction materials, and make estimates and reports on building construction costs (Daryono et al., 2020; Gębczyńska-Janowicz, 2020; Hariyanto et al., 2022). Road and Bridge Construction (RBC) is a skill competency that equips students with the skills to present road and bridge classifications and to draw construction and road and bridge details (Gębczyńska-Janowicz, 2020; Zieliński, 2020). Utilities and Building Construction (UBC) is a skill competency that equips students with the skills to draw a floor plan, cut, view, and detail a building. Make isometric drawings of electrical installations, clean water, dirty water, and rain flows (Puškár, Vráblová & Czafík, 2022; Taraszkiewicz, 2021; Węcławowicz, 2021).

2.3. Skills Competency (C3)

The skills competency subjects are specific vocational content within the scope of the vocational field they are engaged in. Vocational competencies are prepared based on the vocational curriculum by schools and work competencies are according to industry needs by stakeholders. In this case, the vocational field in architectural engineering is the Software Applications and Building Interior (SAB) competency as the dominant graduate competency for architectural engineering (Gil-Mastalerczyk, 2022; Ratajczyk‑Piątkowska & Piątkowska, 2020).

3. Method

3.1. Sample

This research is quantitative with a survey method approach. The research aims to analyze the determinants of competence and to test the competency development model for architectural engineering graduates according to the needs of the construction industry. The research was conducted in the province of Central Java, Indonesia about research by experts in the field of building construction. The characteristics of the research sample are shown in Table 1. Research respondents were selected based on purposive sampling in several fields of construction, namely the fields of buildings, roads, and bridges. This research is quantitative with a survey method approach. The research sample consisted of 240 practitioners and trainers from 40 construction industry companies.

Characteristics

Freq.

Characteristics

Freq.

Gender

Male

153

Specific sectors

Buildings

171

Female

87

Roads

43

Total

240

Bridges

26

Age range

25-30

56

Total

240

>30-35

69

Profile of employer

Director

12

>35-40

52

General Manager

14

>40

63

Project Manager

19

Total

240

Site Manager

26

Educational background

Diploma

77

Senior Engineer

33

Bachelor

115

Senior Drafter/Detailer

34

Master

38

Architect

70

Doctor

10

Estimator

32

Total

240

Total

240

Experience in construction

(year)

<5

41

Construction services business

Limited liability company

71

05-Okt

64

CV

108

>10

135

Individual

61

Total

240

Total

240

Table 1. Research respondents: construction expert

3.2. Research Instruments

The questionnaire contains competency indicators to be assessed by construction experts on the urgency of the 49 proposed competencies based on a 4-point scale: very important (4), important (3), moderately (2), and unrequired (1). In addition, it is also important to know and provide opportunities for experts to express their opinions regarding the current level of urgency of architectural competence required and the demands of graduates to be able to work in the construction industry. Then an open question was added: “Are there any competency indicators that are still lacking according to the needs of the construction industry?” if there are competencies that may not be included in closed questions. The construction of competency measurement is shown in Table 2.

No

Dimension

Elements

Construct

Indicators

References

1

Basic Fields of Expertise (C1)

Basics and Technical Drawing (BTD)

BTD1

Drawing sketch

(Gil-Mastalerczyk, 2022; Makowska, 2021; Puškár et al., 2022; Zieliński, 2020)

2

BTD2

Symbols, notations, and dimensions

3

BTD3

Drawings and building details

4

BTD4

Draw a 3D projection

5

BTD5

Draw the projection using BIM software

6

Building Construction Basics (BCB)

BCB1

Application of Tekla Structures

(Celadyn, 2020; Hariyanto et al., 2022; Li et al., 2019; Simpson & Bester, 2017; Taraszkiewicz, 2021)

7

BCB2

Health and safety in building work

8

BCB3

Wood, concrete, and steel construction

9

BCB4

Material planning in constr uction work

10

BCB5

Implementation of building construction

11

BCB6

Construction work inspection

12

Engineering Mechanics Statics (EMS)

EMS1

Analyze the strength balance of the building

(Daryono, Ramadhan, Kholifah, Isnantyo & Nurtanto, 2023; Hariyanto et al., 2022; McCrum, 2017)

13

EMS2

Analyze the stress on the beam

14

EMS3

Analyze structural elements

15

EMS4

Analyze the moment of the building structure

16

EMS5

Structural planning using SAP 2000

17

Land Measurement Techniques (LMT)

LMT1

Field survey and measurement tools

(Daryono et al., 2020; Gil-Mastalerczyk, 2022; Hariyanto et al., 2022)

18

LMT2

Field measurement sketch

19

LMT3

Water-pass and theodolite

20

LMT4

Total station in building measurements

21

LMT5

Total station in road measurement

22

LMT6

Analyze measurement results

23

Basic Skills Program (C2)

Utilities and Building Construction (UBC)

UBC1

Building plan drawing

(Burke & Parrish, 2018; Puškár et al., 2022; Taraszkiewicz, 2021; Węcławowicz, 2021)

24

UBC2

Building details

25

UBC3

Stair construction drawing

26

UBC4

Piping installation drawings

27

UBC5

Water isometric drawing

28

UBC6

Electrical installation drawings

29

Building Estimation and Costing (BEC)

BEC1

Construction work materials

(Daryono et al., 2020; Gębczyńska-Janowicz, 2020; Hariyanto et al., 2022; Ratajczyk-Piątkowska & Piątkowska, 2020)

30

BEC2

Methods of calculating for construction materials

31

BEC3

Determine the unit price of the building

32

BEC4

The volume of construction work

33

BEC5

Calculating the construction work budget

34

BEC6

Time schedule progress

35

BEC7

Ms. Project for construction cost estimation

36

Road and Bridge Construction (RBC)

RBC1

Classification of roads and bridges

(Daryono et al., 2023; Matusik, 2020; Puškár et al., 2022; Zieliński, 2020)

37

RBC2

Road and bridge drainage

38

RBC3

Drawing of road and bridge construction

39

RBC4

Road and bridge construction details

40

RBC5

Land Desktop for road planning

41

RBC6

ArchiCAD and Revit Architecture for road and bridge construction planning

42

Skills Competency (C3)

Software Applications and Building Interior (SAB)

SAB1

Interior and exterior materials and ornaments

(Gębczyńska-Janowicz, 2020; Gil‑Mastalerczyk, 2022; Łątka & Michałek, 2021; Ratajczyk-Piątkowska & Piątkowska, 2020)

43

SAB2

Autocad for 2D and 3D

44

SAB3

Revit Architecture and ArchiCAD for 3D

45

SAB4

Artificial colors and lighting

46

SAB5

3D rendering using Lumion and V-Ray

47

SAB6

Interior design lay out

48

SAB7

Interior design mockup

49

SAB8

Interior and exterior materials and ornaments

Table 2. Construction of competency measurement for architectural engineering graduates

3.3. Research Design and Hypothesis

In general, PLS-SEM aims to test whether the relationship and predictive effect between constructs. The consequence of using PLS-SEM is that testing can be carried out by ignoring several assumptions (non-parametric) and parameter estimation is carried out directly without the goodness of fit criteria requirements (Al-Fraihat, Joy, Masa’deh & Sinclair, 2020; Apriliani, Widihastuti, Daryono, Jaya & Rizbudiani, 2023). In this study, the PLS-SEM technique was used to test the structural model because of its great complexity with many constructs and indicators, there are 3 measurements, 8 constructs, 49 indicators, and 9 relationships. In addition, the coefficient of determination is used to estimate the accuracy of the model construct.

Based on the explanation of skill competencies in Basic Fields of Expertise (C1), Basic Skills Program (C2), Expertise Competencies (C3) that must be mastered by architectural engineering graduates according to the demands of the construction industry to work, this study formulates the following hypothesis: H1, H2, H3, H4. Competencies in BTD, BCB, EMS, LMT positively affect the Basic Fields of Expertise (C1) as competence demands on current architectural engineering graduates. H5, H6, H7. Competencies in BEC, RBC, UBC positively affect the Basic Skills Program (C2) as competence demands on current architectural engineering graduates. H8, H9. Competencies in C1 and C2 positively affect Skills Competency (C3/SAB) as competence demands on current architectural engineering graduates. The structural model in PLS-SEM in the path diagram of the relationship between construct variables and latent variables as a determinant of the competence of architectural engineering graduates is generally shown in Figure 1.

Figure 1. The research model framework

3.4. Data Analysis

Interpretation of measurement data based on evaluation of measurements and structural models. Evaluation of measurement model (Al-Fraihat et al., 2020; Daryono et al., 2023; Dash & Paul, 2021; Hair, Howard & Nitzl, 2020; Hariyanto et al., 2022; Supriyanto, Munadi, Daryono, Tuah, Nurtanto & Arifah, 2023): (1) Internal consistency reliability (>0.70): using the indicator of Cronbach’s alpha (α), rho_A (φ), and Composite Reliability (δ). (2) construct validity: (a) convergent validity using the indicator of Factor Loading (λ >0.70) and AVE (≥0.50); and (b) discriminant validity using the indicator of Fornell-Larcker (each construct is greater than the correlation with another construct). Evaluation of structural model (Apriliani et al., 2023; Hair, Ringle, Gudergan, Fischer, Nitzl & Menictas, 2019; Hair, Howard & Nitzl, 2020; Khan, 2021; Law & Fong, 2020): effect size (ƒ²); coefficient of determination (R²); predictive relevance (Q²); path coefficient (β-coefficient, ρ-value; and T-statistics); and model’s fit (SRMR ≤0.08; NFI >50%; and RMSTheta ≤0.12).

4. Findings

4.1. Preliminary Study

In the initial stage before evaluating the structural model, the evaluation of measurement is carried out first to ensure the convergent validity of the constructed model on each competency indicator. Convergent validity using the indicator of FL 0.70, if <0.70 then the indicator is eliminated from the constructed model. Based on the first run in the PLS Algorithm, totaling 49 indicators, 2 indicators failed on FL elimination <0.70. First, the Utilities and Building Construction (UBC) construct, namely the UBC4 indicator on the competence of presenting the specifications of piping installation, obtained a FL value of 0.659. The Building Estimation and Costing (BEC) construct, which is the BEC1 indicator of the competence of presenting the specifications of construction work materials, gets a FL value of 0.573. So, the two indicators are not included in the next stage, namely the evaluation of the structural model. Finally, there are 47 valid architectural engineering competency indicators for the evaluation of the measurement and structural model testing.

4.2. Construct Validity: Convergent Validity

Based on Table 3, the overall factor loading value for each indicator is >0.70 (0.730-BEC7 to 0.899-UBC1 & UBC2). The AVE value for each dimension has a value of >0.50 (0.599-SAB to 0.714-UBC). So it can be concluded that each indicator and dimension on the instrument has supported the convergent validity requirements. This means that the level of relationship between indicators and dimensions can be explained by 73.00% to 89.90%.

Based on the value of the loading factor coefficient, the most dominant statement indicators represent the successful competence of architectural engineering graduates namely UBC1 & UBC2 with the statements “Building plan drawing” and “Building details” on the Utilities and Building Construction (UBC) dimension of 89.90%. Meanwhile, the weakest indicator in measuring the success of architectural engineering graduate competencies is BEC7 with the statement “Ms. Project for construction cost estimation” in the organizational dimension of 73.30%.

No

Indicators

Construct

Convergent Validity

Internal Consistency Reliability

VIF

<5.00

FL (λ>0.70)

AVE (>0.50)

CA (α>0.70)

rho_A (φ>0.70)

CR (δ>0.70)

1

Basics and Technical Drawing

BTD1

0.818

0.676

0.888

0.886

0.912

2.198

2

BTD2

0.834

2.432

3

BTD3

0.846

2.646

4

BTD4

0.797

2.174

5

BTD5

0.814

2.306

6

Building Construction Basics

BCB1

0.825

0.671

0.902

0.907

0.924

2.395

7

BCB2

0.792

2.178

8

BCB3

0.812

2.265

9

BCB4

0.806

2.181

10

BCB5

0.832

2.547

11

BCB6

0.846

2.757

12

Engineering Mechanics Statics

EMS1

0.797

0.654

0.868

0.870

0.904

2.124

13

EMS2

0.832

2.437

14

EMS3

0.810

2.301

15

EMS4

0.788

2.061

16

EMS5

0.818

2.142

17

Land Measurement Techniques

LMT1

0.781

0.656

0.895

0.898

0.920

2.09

18

LMT2

0.863

3.32

19

LMT3

0.789

2.353

20

LMT4

0.791

2.363

21

LMT5

0.781

2.117

22

LMT6

0.850

3.222

23

Utilities and Building Construction

UBC1

0.899

0.714

0.899

0.904

0.926

3.234

24

UBC2

0.899

3.385

25

UBC3

0.790

1.934

26

UBC5

0.828

2.170

27

UBC6

0.804

2.137

28

Building Estimation and Costing

BEC2

0.849

0.663

0.898

0.905

0.922

4.648

29

BEC3

0.894

4.583

30

BEC4

0.800

2.982

31

BEC5

0.745

1.751

32

BEC6

0.856

4.827

33

BEC7

0.730

1.972

34

RBC1

0.819

2.287

35

Road and Bridge Construction

RBC2

0.809

0.678

0.905

0.906

0.920

2.069

36

RBC3

0.839

2.688

37

RBC4

0.783

1.948

38

RBC5

0.823

2.317

39

RBC6

0.865

2.763

40

Software Applications and Building Interior

SAB1

0.739

0.599

0.904

0.907

0.923

1.939

41

SAB2

0.804

3.714

42

SAB3

0.751

1.886

43

SAB4

0.745

1.882

44

SAB5

0.749

1.906

45

SAB6

0.815

2.448

46

SAB7

0.776

2.273

47

SAB8

0.809

3.418

Table 3. Convergent Validity and Reliability

4.3. Construct Validity: Discriminant Validity

Based on the results PLS Algorithm in Table 4, the value of the Fornell-Larcker Criteria for each construct (BTD, BCB, BEC, EMS, LMT, RBC, SAB, UBC) is greater than the correlation with another construct. In the EMS construct, the FLC value is 0.809, which is greater than the correlation with another construct, namely EMS→LMT of 0.008, EMS→RBC of 0.027, EMS→SAB of 0.049, and EMS→UBC of 0.292. The value of cross-loading at the output of Table 4 ranges from 0.797 to 0.899 (>0.70). Because all indicators have a larger outer loading value with their construct compared to other constructs, this model has met the requirements of discriminant validity. The Heterotrait-Monotrait (HTMT) value obtained in the PLS Algorithm run is at least <0.9 (Al-Fraihat et al., 2020; Kurup, Li, Powell & Brown, 2019) so the discriminant validity testing of all constructs has certainly been fulfilled in measuring the competency of architectural engineering.

Indicators

BTD

BCB

BEC

EMS

LMT

RBC

SAB

UBC

BTD

0.822*

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

BCB

0.152*

0.819*

 

 

 

 

 

 

0.170**

 

 

 

 

 

 

 

BEC

0.226*

0.285*

0.814*

 

 

 

 

 

0.254**

0.313**

 

 

 

 

 

 

EMS

0.181*

0.223*

0.126*

0.809*

 

 

 

 

0.204**

0.244**

0.175**

 

 

 

 

 

LMT

0.054*

0.034*

0.127*

0.008*

0.810*

 

 

 

0.111**

0.082**

0.155**

0.094**

 

 

 

 

RBC

0.237*

0.237*

0.064*

0.027*

0.078*

0.823*

 

 

0.264**

0.261**

0.123**

0.110**

0.105**

 

 

 

SAB

0.125*

0.197*

0.333*

0.049*

0.710*

0.232*

0.774*

 

0.283**

0.193**

0.127**

0.324**

0.206**

0.223**

 

 

UBC

0.255*

0.179*

0.111*

0.292*

0.188*

0.209*

0.300*

0.845*

0.144**

0.220**

0.382**

0.117**

0.786**

0.260**

0.328**

Note: *fornell-larcker; ** HTMT

Table 4. Discriminant validity: correlation matrix of fornell-larcker and HTMT

4.4. Internal Consistency Reliability

This measurement aims to estimate how much each construct can assess the latent variable, namely the demands of architectural competence. The value of each measurement is considered reliable and must be above 0.70. Based on the output PLS Algorithm of Table 3, it is found that all constructs have values α = 0.868 to 0.905, rho_A = 0.886 to 0.907, and C.R. = 0.904 to 0.926. This test concludes that all construct measurements get values >0.7. So, it can be said that all constructs for measuring the competence of architectural engineering graduate students have been reliable. The measurement of the evaluation model are shown in Figure 2.