Modelling Research Competence in Social and Engineering Sciences at Master’s Level Programs: A Scoping Review

Abstract

The research–teaching nexus in higher education has been strongly discussed and debated, especially when it comes to developing research competence and introducing evidence-based practice into the master’s degree curricula for Educational Sciences and Engineering Sciences. Previous systematic reviews have summarised the manner in which research is taught in higher education, and revealed that there is a lack of cross-disciplinary comparative analysis in research–pedagogy in various scientific disciplines, as well as in assessing and measuring the development of research competence (RC) at the level of higher education. To provide a comprehensive picture of the RC development and of the teaching RC, a scoping review (SCR) methodology was performed. For the purpose of the present study, a total of 33 research articles were analysed to investigate RC development in Engineering and in Social Sciences. RC is regarded as a core competence in Engineering Sciences, while in Educational Sciences, it is not yet a standardised concept. Despite differences in Social and Engineering studies, the review revealed some common aspects concerning RC modelling, based on specific key skills that students are supposed to acquire at the master’s degree level. This SCR draws our attention to the complex process of RC development as a long process requiring practice and activities implemented throughout the entire higher education process, regardless of scientific field.

1. Introduction

In recent years, research has become a priority in higher education policies and RC is currently one of the most important capabilities to acquire. Research has been the driving force of many remarkable advances [1], and it is crucial to becoming able to respond to the increasingly diverse and flexible environment of the global and knowledge-based contemporary society [2]. Why is it important to develop RC, starting from pre-university education to university programs? It is because RC enables a deeper understanding of the investigated issues. RC is regarded as a core competence in Engineering Sciences, while in Educational Sciences, it is not yet a standardised concept. Higher education institutions are the most suitable providers of “research-based education” [3] (p. 561). The research–teaching nexus in higher education has been strongly discussed and debated [4], especially when it comes to developing RC and introducing evidence-based practice into the master’s degree curricula for Educational Sciences and Engineering Sciences. Research is likely to contribute substantially to future developments in Educational and Engineering fields [1]; therefore, connecting research and university teaching is a priority. Master’s studies should aim at the acquisition of RC, as master’s students should have a greater level of scientific reasoning and various educational opportunities to utilise proper scientific reasoning, including “hypothetical–deductive reasoning, control of variables, proportional, correlation, and probabilistic reasoning” [5] (p. 632). However, scientific literature states that there are no comprehensive tools to assess the acquisition of RC for Social Sciences during higher education programs. Therefore, the tools one can use to assess RC remains a key point of concern for universities, and this issue is currently a major theme in the field of master’s degree preparation, and how to distinguish master’s-level programs from undergraduate or doctoral studies.

1.1. Approaches to Modelling and Teaching Research Competence in Higher Education

RC is a complex concept; however, it has received little attention so far [6]. The complexity of RC is determined by the need to practice various components: cognitive, reflective, activity-based and motivational skills. According to Böttcher & Thiel [6], RC competence can be defined either from the perspective of a specific academic discipline or from a cross-disciplinary approach. According to Dekker [7], RC falls into one of three groups: ‘generic’ competences, those related to ‘using research’, and those related to ‘doing research’. Some researchers [8,9] distinguish between receptive RC, that is referring to the ability to read and comprehend the existing research findings, and active RC, which is the result of an active engagement in generating research findings, both essential to create new knowledge based on scientific methods [10]. For professionals working on developing RC in students, modelling scientific reasoning, mastering methodological knowledge, research techniques and readiness to use them in professional activity represents the main aim in teaching research. It ensures a quality teaching–learning experience [11]. The set of skills necessary to acquire RC consists of specific abilities to search, evaluate and analyse sources on the research topic, formulate appropriate (research) questions, academic writing, preparation and delivering oral presentations on research findings. Nonetheless, Böttcher & Thiel [6] view the process of RC modelling focused on a specific discipline and/or area, and lacking perspective analysis for cross-disciplinary approaches. Research literacy is part of the objectives for obtaining higher education degrees and it is also found in master’s-level programs in Educational Science [3]. Healey [12] categorised four different ways that it enables research-teaching interrelation: (a) research-tutored teaching, (b) research-led teaching, (c) research-based teaching, and (d) research-oriented teaching.

1.2. Development of Research Competence in Engineering Sciences

Courses on research in Engineering Sciences focus more on providing students with hands-on experience in the conducting of research rather than research dissemination or academic writing. However, teaching research skills, such as research reasoning, academic writing or research methodology also has a positive effect on developing engineering skills, mostly by learning opposed aspects of thinking (creative, “out-of-the-box” thinking), required by today’s engineering. The Engineering Studies curriculum focuses on interdisciplinary cooperation based on increased opportunities for students to learn about different perspectives on knowledge production, to increase analytical skills, to practice critical thinking, intellectual independence and to develop self-confidence. RC is one of the core components of the engineering profession. During research teaching activities, students can implement the research approach in different fields of activity and apply it in various contexts. This confirms the fact that RC is marked by versatility, multifunctionality and “super-disciplinarity” [13]. In Engineering Sciences, some aspects of RC are getting special attention, such as (1) developing students’ ability to identify and solve research problems; (2) developing literacy skills enabling them to search, process, systematise and synthesise scientific information; (3) creating significant products of the research activity and (4) effectively communicating scientific results [14,15]. Some curricula in Engineering Sciences offer excellent research opportunities to master’s students and are internationally recognized for facilitating the understanding of research process and scientific method. In order to develop RC, the learning process should follow all the stages of a research process.

1.3. Development of Research Competence in Social Sciences

Commonly, RC development in Social Sciences curricula has concentrated increasingly more on the research process, that is, on the design and research implementation, and less on the results interpretation, inferring analysis and research findings transfer and application [10]. At the master’s level, in Social or Educational Sciences, research is taught during a specific course, separated from other courses or other educational activities, with an emphasis on working with scientific literature [3], and preventing students from applying the content in the educational practice. The time available to obtain a meaningful research experience is perceived to be short [1], and faculty are concerned about succeeding in inspiring and building RC for all students in undergraduate and master’s programs [1]. Moreover, Educational Sciences programs struggle in providing research opportunities as the curricula is already packed with development of communication, attitudinal, behavioural management, teaching and assessment skills, putting RC somehow aside. Master programs are focused mainly on educational practice and little on RC development. However, studies [9,16] state the need to develop research skills, such as critical reasoning, defining and conducting an appropriate literature search, improving teaching practices and learning outcomes, synthesizing findings, and drawing conclusions from findings and applying evidence-based teaching in educational activity. Research literacy for Social and Educational Sciences implies the ability to actively search relevant and solid information, the ability to ask questions and identify in scientific literature the information required to answer specific scientific questions, and the ability to comprehend and reflect on scientific knowledge, including the ability to infer, draw conclusions and take evidence-based decisions for educational issues [3,9].

1.4. Research Aims and Research Questions

Previous systematic reviews summarised the manner in which research is taught in higher education (specifically in Medical Sciences) and revealed that there is a lack of cross-disciplinary comparative analysis in research–pedagogy in various scientific disciplines, as well as in assessing and measuring the development of research competence at higher education level. The political, educational and socio-economic environment is changing rapidly, shifting to more digitalised and technologically-mediated interaction. In response to a dramatically changing environment and labour market, educational institutions have to adapt to better respond to societal needs and provide a high-quality education. Numerous studies are trying to help universities in this process, yet with regards to master’s studies, there is a limited body of research. Moreover, evidence-based decisions are crucial to any field, and preparing students for the unknown future should be done by developing, to a great extent, students’ RC. Therefore, in undertaking this review, we aimed at identifying how RC is defined and how it is constructed and developed within master’s degree studies in Engineering and Social Sciences. The review will help us learn from the existing evidence about the effectiveness and the methodological aspects in developing RC of students to inform future programme and policy making. To reach this major objective, three research questions have been raised:

RQ1:

How is research competence defined in Social and Engineering Sciences and how is it developed for future teachers and future engineers, within the higher education context

RQ2:

What were the major purposes, methodologies and outcomes of developing research competence during master’s studies over the past decade?

RQ3:

What are the dimensions commonly used to assess the research competence of master’s students?

The methodology followed for this scoping review can be found below.

2. Methodology

A SCR methodology was performed to define the concept of RC, to map out how it is developed during master’s studies. To obtain a comprehensive picture of the process and the didactic methodology used to support master’s students, we followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology—PRISMA [17] and the Cochrane Handbook for Systematic Reviews and Interventions [18].

The PRISMA methodology comprised several steps:

(i)

Determining selection and exclusion criteria for the article sample identification.

(ii)

Setting quality criteria established for the systematic mapping of literature on RC development.

(iii)

Formulating clear questions and explicit methods to analyse the data from the studies that are included in the review.

The review team comprised four researchers, all from Engineering and Educational Sciences, with a particular focus on research. They prepared a literature review protocol and undertook the review work between May and August 2022.

2.1. Search Strategy

For the purpose of conducting the present SCR of the international multidisciplinary academic literature, the Web of Science (WOS) and SCOPUS electronic databases were selected. Initially, the search of specific terms (RC, master programs research) was undertaken in titles, keywords and in the article abstracts.

• WOS: TS = ((“research competence*” OR “research ability*” OR “research skill*”) AND (“higher education” OR “university*” OR “master*”))
• Scopus: TITLE-ABS-KEY = ((“research competence*” OR “research ability*” OR “research skill*”) AND (“higher education” OR “university*” OR “master*”)).

2.2. Study Selection

The selection process of articles for our study comprised a fast screening of the latest studies done on RC. A total of 889 articles were identified.

Inclusion and exclusion criteria:

To select relevant studies for our study aim, several inclusion and exclusion criteria had been established and validated by a group of experts in research methodology (two university professionals in Educational Sciences, one university professional in Engineering Sciences, and one expert in Statistics) (

Table 1. Inclusion criteria and exclusion criteria.

Inclusion Criteria:
Study on the RC of students (and/or teachers) development in the context of master’s programs. Theoretical approach in the development of RC in higher education Timeline of research from 2012 until 2022. The research follows a strong research methodology with relevant outcomes. Comparative analyses are preferred. Research master’s degree educational programs
Exclusion Criteria:
The articles are not related to the research competencies of students in the context of higher education. The articles do not explore RC in Social Sciences and Engineering higher education programs. The articles do not follow the appropriate structure of a research according to the research method.

).

2.3. Quality Criteria

For our SCR, the quality criteria targeted the model of how RC is developed, the profile of competences necessary to undergo research during master programs, relevant input to research questions formulated for this SCR, valuable recommendations for future development of RC for master’s students, and forecasting future research trends (see

Table 2. Quality Criteria.

Quality Criteria
Definition of RC. Development of RC during master’s studies. Assessment of RC of master’s students. The profile of RC of a master’s degree student. The exploitation of RC of master’s students during their studies.

). The quality criteria had been validated and coded by a group of experts for an efficient selection of articles. The process of identifying the most appropriate papers was challenging, mostly, because there are not so many comparative studies on RC development. Studies in Engineering Sciences do not focus on the teaching process of RC, therefore, in order to build up an understanding regarding the process of RC modelling, studies across other disciplines had been also included.

2.4. Synthesis Methods

The data were synthesised using Nvivo 12.0 software, based on a thematic matrix [19] and co-word analysis [20] and focused on identifying the main outcomes and contributions of the selected publications for SCR, as well as exploring the modelling of RC and the evolution of it in Engineering and Social Sciences. Thematic matrix and co-occurrence analysis are types of quantitative analysis used to analyse the content of selected papers by determining keyword co-occurrence rates and relationships of co-words, to ease the synthesis of an extensive amount of data. Their main premise in using keywords frequencies rests on the assumption that thematic and co-word analysis reflect the main content of publications [21], as being adequate descriptors of the papers’ content. Afterwards, keywords can be regrouped using statistical techniques such as cluster analysis or factor analysis, drawing attention to “particular research hotspots’’ [22]. To provide a comprehensive analysis of selected studies, main theme and sub-themes identified had been coded by a reviewer and a second reviewer checked the study sample and validated the coded system, ensuring a monitoring process regarding the consistency across the articles.

3. Results

For this review, 33 research articles were analysed, in which RC was investigated in Engineering and Social Sciences. As a result, we found that RC is defined based on several models and consists of a variety of skills and competences; moreover, its scope is wide, as is its background: from information literacy and evidence-based decision to information management and communication. First, the SCR results show the landscape of the studies that focus on RC modelling in higher education, particularly at the master’s degree level, materialised in a quantitative summary of the SCR sample. The main characteristics relevant for our aim and research questions were geographical location, educational level, and study program. Afterwards, the results report on the type of research design across the selected papers and the main key points emerging from the studies based on the research questions posed by this SCR. We concentrated on the significant themes generated by the SCR, including an exploration of the RC models and profiles used in higher education, the main features of the RC developed and exploited during their master’s degree studies or after graduation, and how the RC of master’s students is assessed.

3.1. Study Selection

The process of article selection is presented in the PRISMA flow diagram from Figure 1. During pre-screening, 889 papers were identified. After title screening and deleting duplicates, 257 studies were kept for further analysis. At this stage, two reviewers screened the abstracts of the selected papers, based on exclusion criteria. Independent full-text assessment, based on the eligibility, resulted in a sample of 26 articles. After skimming the reference list of the selected papers, another seven papers were added.

Descriptive statistics of the occurrence of various terms used to describe RC was undertaken after the literature analysis, focusing on various terms used to describe RC, as well as its content and components identified in the selected articles. An interpretative summary of the terms used and their connection to the background domains followed after the descriptive statistics phase.

3.2. Study Characteristics

The 33 articles included in the review are journal peer-reviewed papers, undertaken across Asia (n = 7), North America (n = 3), Europe (n = 12), Australia (n = 1) and not specified regions (n = 10). As a transdisciplinary area of study, RC can be found within and across a diverse range of disciplines such as Social Science (n = 9), Education (n = 7), Health (n = 3), Computer Science (n = 2), Engineering (n = 6), Linguistics (n = 2), as well as others or fields not specified (n = 13).

The results of the included studies were categorized into factors related to answering our research questions and research objectives (see

Table 3. Characteristics of SCR-selected studies.

Authors	Study Design	Data Collection	Geographical Area	Research Sample	Discipline of Studies	Observations
Ciraso-Calí et al. [23]	Case study approach	Content analysis, survey study, and Delphi technique.	Spain	Pedagogy and Social Education at the Universitat Autònoma de Barcelona	Educational Sciences	Communicative skills and state-of-art reviewing skills are the least present across the courses
Castillo-Martínez & Ramírez-Montoya [24]	Systematic review	Preferred Reporting Items for Systematic Reviews and Meta-Analyses—PRISMA	Not applicable	N = 42 articles	Educational studies	Absence of studies about research skills to develop academic literacy through innovative models
Zhao et al. [25]	Systematic literature review	PRISMA	Not applicable	N = 33 articles	Higher Education	Digital competence used in research
Leshchenko et al. [26]	Pedagogical experiment	Questionnaire on digital skills	Ukraine	N = 8 (Ukrainian universities) N = 222 (postgraduate and doctoral students), and N = 58 (scientific and pedagogical Workers)	Postgraduate and doctoral programs, Scientific field of the programs are not specified	Assessment of digital skills and use of digital technology in research activity
Berndt et al. [27]	Explorative, cross-sectional design	Online test battery	Germany	N = 212	Medicine, Social Sciences, Economics	Many higher education curricula are allegedly not providing sufficient support to foster students’ statistical literacy and scientific reasoning and argumentative skills
Borg [8]	Review	Critical analysis	Not applicable	Not applicable	Language teachers	Research engagement is recommended as a potentially productive form of professional development and a source of improved professional practice
Sudirman et al. [28]	interpretive/qualitative research	Open-ended interviews	Indonesia	N = 28 research proposals of students	Linguistics	Challenges in academic writing
Qayoom et al. [29]	Cross-sectional analysis	Survey	Saudi Arabia	N = 20 undergraduates	Humanities Studies	Assessment of academic writing skills
Miniyarov & Yaitskiy [30]	Experimental design	Critical analysis	Russia	N = 182 students	Biological Sciences	Development of a criteria-based assessment system and a methodological model for establishing of research competence of biology students
Asplund & Grimheden [31]	Quasi-experimental design	Mixed methods	Sweden	Not specified	Engineering Master Program	Transfer research knowledge to engineering practice
Koletvinova & Bichurina [32]	Observational and experimental study	Survey	Kazan (Volga Region)	N = 80	First-year students in Psychology and Education	The development of research competence of students depends on many factors
Skurikhina et al. [14]	Observation, pedagogical experiment	Survey	Russia	School Students	Educational Robotics	School students’ research competence formation by means of robotics
Böttcher & Thiel [6]	Cross-sectional and longitudinal study	Construction of an assessment instrument of RC	Germany	N = 391 university students	Various academic disciplines, Bachelor, Master or PhD program.	The development of RMRC-K-RC model
Hatziapostolou et al. [33]	Experimental design	Self-assessment surveys	Greece	Not specified	Advanced Software Engineering.	Through a research experience, students can not only advance their research skills, but also strengthen their employability profile
José Sá & Serpa [34]	Review	Bibliographical research	Not applicable	Not applicable	Higher Education	Transversal competences
Gorshkova [13]	Experimental design	Testing, surveys, ranking, self-assessment, observation, analysis of various students’ paperwork	Russia	N = 1520 (1390 students and 130 professors)	Engineering Students	The students showed statistically significant changes in the maturity levels of all components of the research competence
Gess et al. [35]	Cross-sectional study	Differential Item Functioning (DIF)	Germany	Higher Education	Social Sciences (Political Science, Educational Sciences and Psychology)	Psychology students showed relative strength in quantitative methods, students in other subjects in qualitative methods
Banevičiūtė & Kudinovienė [36]	Qualitative design	Literature review and interviews	Lithuania	N = 12 first-year students N = 15 s-year students	Arts Education master’s	Some research skills are challenging
Gould [37]	Review	Literature analysis	United States	Not specified	Mathematics and Science	Development of CART algorithm
Spelt et al. [38]	A multidimensional approach	Interviews	The Netherlands	N = 615 students	Natural Sciences and of Social Sciences	Interdisciplinary thinking
Sharma [39]	Review	Literature analysis	Not applicable	Not applicable	Sciences	How to form statistical literacy
Chang et al. [40]	Review	Literature analysis	Not applicable	N = 588 studies	Medical Sciences	Six hotspots of domain research were identified.
Ding et al. [5]	Cross-sectional study	Lawson’s Classroom Test of Scientific Reasoning	China	N = 1637 students	Physical Sciences (Physics and Chemistry), Engineering (Electrical and Computer Engineering), and Education	Scientific reasoning assessment and comparison
Tevanovna & Aramovna [41]	Review	Critical analysis	Russia	Not applicable	Higher Education	Developing new standards of research teaching
Davidson & Palermo [42]	Cross-sectional study	Survey (Research Skills Questionnaire)	Australia	N = 46 students	Bachelor Nutrition and Dietetics and Bachelor Nutrition Science	Enhancing students’ research skills
Groß Ophoff et al. [3]	Cross-sectional and longitudinal	The test items were selected from the item pool of the main study and distributed in two tests booklets	Germany	N= 6 (German universities)	Educational Science (Early Education)	Monitoring students’ development during courses on research methods in educational science (Information Literacy, Statistical Literacy, and Evidence-based Reasoning)
Hartmann et al. [43]	Cross-sectional validation study	Standardized paper-and-pencil test on scientific reasoning	Germany Austria	N = 2.247 (bachelor and master’s students)	Natural Sciences, Educational Sciences	Development of a scientific reasoning competence test
Fischer et al. [44]	Review	Literature analysis	Not applicable	K-12 and higher education.	Not specified	Differences between disciplines are neglected by literature
Earley [45]	Review	Literature analysis	Not applicable	N = 89 studies	Higher Education	A lack of research on assessment and on what and how students learn in research methods courses
Marz et al. [1]	Transnational cross-sectional study	Survey	29 European & 13 non-European countries	Bachelor, Master, Doctorate	Medical Sciences	A consensus between stakeholders about core competences relating to research for each of the three Bologna cycles
Fleming et al. [46]	Mixed methodologies	Post-experience surveys to collect self-report data	United States	N = 233 students	Engineering, Architecture and Computer Science	Research experiences of students abroad
Burke et al. [47]	Review	Theoretical analysis of the curriculum	United States	University of Pittsburgh	Bachelor of Science in Nursing, Master of Science in Nursing, and Doctor of Philosophy programs	Recommendations on how to modify the curriculum

).

Firstly, the reviewing process revealed that RC is a complex concept, understood slightly differently across programs, studies and level of education. RC modelling includes the following dimensions: (1) research skill development (methodical, methodological and research process knowledge; research traditions such as quantitative methods, qualitative methods, and research process knowledge contingent to both traditions (2) research supervision, (3) self-learning capacity, (4) time management, (5) presence of research environment and (6) infrastructure and funding. Both Engineering and Social Sciences are expected to provide content-specific knowledge regarding the research domain, required to competently conduct a research project. The review of the selected papers revolves around three types of knowledge: (1) research process knowledge (problem identification, research planning, data analysis and interpretation), (2) methodical knowledge and (3) methodological knowledge [35]. In addition, some important aspects of RC are the development of a researcher’s mindset [9], metacognitive competences [9] academic writing skills and the distribution of research findings.

4. Discussions

Our findings demonstrate clearly that research is considered as a core competence in higher education and a driving force for societal development. Therefore, there is a great interest in developing RC. Across the reviewed papers research was described as a complex yet important phenomenon, and as a crucial asset in contributing to societal development. We use this section of the review to discuss the implications of the findings identified in the selected papers and implications for further development of RC in higher education.

How is RC defined in Social and Engineering Sciences and how is it developed for future teachers and future engineers, in the higher education context (Research Question 1)?

To answer our first research questions, on how RC is defined in Social and Engineering Sciences and how it is formed for future teachers and future engineers in the context of higher education, we collected the views on RC from the selected articles. The most frequently used terms, based on the data of this review, was RC [33], research skills, information literacy, and research literacy. Research and RC are described as vital to societal progress and is viewed as a lengthy process but significant and valuable to getting knowledge [48]. As Wessels [9] argues, RC building in Educational Sciences rely more on working with application-oriented research question based on the available literature, and less in conducting empirical research, as in Engineering Sciences. This review provides rich descriptive indicators of what RC could mean (see

Table 4. Criteria and indicators of research competence.

Research Competence Dimensions	Research Abilities	Studies
Content knowledge	- Critical thinking - Scientific reasoning - Scientific argumentation - Critically evaluate empirical studies, including quantitative, qualitative, and mixed-methods studies - Awareness of available digital technologies to support research	Ding et al. [5]; Hartmann et al. [43] Fischer et al. [44] Burke et al. [47]
Skills in reviewing scientific literature	- Ability to analyse current research - Keep track of the pertinent scientific literature - Critically appraise relevant evidence-based literature - Mastery in working with scientific literature - Ability to compile bibliographic lists - Searching and storing data - Define and carry out an appropriate literature search	Burke et al. [47] Marz et al. [1]
Methodological skills	- Design research - Application-oriented research question - Collect data and identify research questions - Apply research principles - Statistical analyse (knowledge of mathematical and statistical methods of processing research data) - Apply ethical principles and analysis to research, seeking ethical approval where appropriate	Gess et al. [35]; Wessels et al. [9] Berndt et al. [27]; Gould [37]; Sharma [39] Marz et al. [1]
Skills in interpreting research results	- Scientific reasoning and scientific argumentation - Synthesising and analysing research findings - Drawing conclusions - Evidence-based reasoning - Improving professional practice by taking evidence-based decisions - Interpretation of results and application of findings - Evaluative-reflexive self-reflection, self-assessment of own research activity and received scientific results	Ding et al. [5]; Fischer et al. [44] Marz et al. [1] Groß Ophoff et al. [3]; Burke et al. [47] Gess et al. [35]; Wessels et al. [9]
Communication skills	- Academic writing - Ability to present research results (obtained by others and theirs) - Ability to use open digital scientific and educational systems to search and store - information	Böttcher & Thiel [6]; Qayoom & Saleem [29]; Sudirman et al. [28] Marz et al. [1]
Value-motivational and ethical skills	- Motivation to participate and engage in science - Appropriate attitudes towards scientific progress	Leshchenko et al. [26] Borg [8]; Wessels et al. [9]

). It comprises theoretical research skills (searching skills, skimming strategies, deep-reading skills, analysing and synthesise scientific literature abilities); finding and defining a research problem, ability to address relevant research questions and formulate research hypotheses [10]; inquiry-based learning so that students can learn how to develop questions, solve problems, acquire insights methodically and reflect critically on questions of principle [49]; epistemic curiosity or insights on how knowledge is generated, on research methodologies and on research methods [9]; empirical skills (elaborating and selecting appropriate research instruments, abilities in analysing and interpreting research findings, abilities in formulating conclusion and disseminating the results) [36]; metacognitive competences (ability to reflect, monitor and control’ own cognitive functions); epistemological beliefs (the structure of scientific knowledge and the origin of scientific knowledge) [9]; critical reflection; receptive RC (“engagement with the research”) (information literacy, statistical literacy (competent data management), critical thinking (the evidence that is identified must be assessed and conclusions must be drawn from the interpreted information) [9]; understanding and applying research results [35]. There is little data on necessary prerequisites of the research courses for master’s students in order to facilitate the modelling of RC [47].

What were the major purposes, methodologies and outcomes of developing research competence during master’s studies over the past decade (Research Question 2)?

Studies [1] identified a great disparity among study programs, higher education institutions and countries regarding the process of development of RC. The general pedagogical pathway consists in providing a methodological course on research (during first and second cycle), finalised with writing and defending a thesis (depending on the study program). The disparity is spotted in the time invested in creating research opportunities (for example, in Netherlands, at least 4–6 months (full time) duration is dedicated to master’s thesis preparation, while in Romania, there is no specific full time dedicated to this process at least for Social Sciences [50]). Students’ RC is typically taught in discipline-specific learning environments, such as specific research methods courses for students enrolled in Psychology or Educational Studies [51]. Wessels et al. [9] highlights the need to foster researcher’s mindset, which implies that students should be able to utilise largely theoretical knowledge acquired during their studies in order to analyse the professional field, as well as take evidence-based decisions in their own professional activity, in a critical reflexive manner [9]. Being able to ask appropriate research questions and to look for the appropriate answers in scientific literature is a prerequisite to pursue master’s level programs. Recalling knowledge, applying knowledge, evaluating research projects, providing research-related opportunities to perform social-scientific research are the main directions identified across the selected papers. Burke [47] considers that during the first year of courses, students are expected to develop searching skills, skimming strategies, deep-reading skills, analyse and synthesise scientific literature, so that they become competent in accessing, identifying and assessing relevant data in the scientific literature. Afterwards, due to teaching research modules, students begin to identify and define research problems and become able to identify research questions and formulate research hypotheses [10], search for the evidence related to the specific problem, be competent in handling of data (“statistical literacy”) [27,37,39], synthesise findings and be able to infer and draw relevant conclusions. Modelling RC involves other abilities such as designing a study, performing statistical analyses, and academic writing to disseminate research results. Research pedagogy has two aims when it comes to teaching science: to enable future educators and engineers to ‘use’ research and to enable them (or at least stimulate them) to ‘do’ research (in academia or in another professional context). RC components are important to the design of a master program curriculum. Faculty develop research opportunities for students and provide necessary equipment and research infrastructure required for master’s thesis completion. The modelling of research skills for Social and Engineering Sciences students begins at undergraduate level and continues to master’s level, yet there is a gap in differentiating the content and amount of research hours at master’s level, as well as effective research teaching and assessment. Master’s level students should have more extensive opportunities to practise their research skills in accessing and searching scientific literature, developing scientific reasoning, and critically approaching the data-based literature.

The content and definition of research competence for Engineering and Social Sciences.

Studies show different research methodological approaches between Engineering and Social Sciences for competence-oriented teaching. The content of the research course is summarised in connection to different approaches based on the articles reviewed. This SCR provide some characteristics of RC that appear relevant in the teaching process: critical thinking [5,43], scientific reasoning [5,27,43], scientific argumentation [5]. Faculty are encouraged to make their students aware of available digital technologies to support research and to create the necessary conditions where all required skills could be practiced. RC consists of the following elements: (1) technical skills and practices in using research instruments, statistical apps and other data analysis and synthesis aids; (2) abilities to use and apply scientific reasoning, deep-reading and critical thinking in a meaningful way and be able to select appropriate methods, instruments and techniques for the research process in general. The emphasis is laid strongly on knowledge-related skills and competences; (3) abilities to understand the research philosophy that integrates various disciplines and refer to ethical issues, the critical use of scientific outcomes and the goal of pursuing truth and (4) motivation to participate and engage in science and include appropriate attitudes towards scientific progress. Within the Engineering master’s, the amount of time (14–30 ECTS) on mandatory research courses is significantly higher than for Social Sciences master’s programs, in addition there is a full-time research project for at least 4 months that all engineering students do before obtaining a master’s degree.

The challenges of research teaching identified in the SCR referred to the lack of availability of time, supervisor competence, technical support, and adequate funding to purchase chemicals and avail services [52]. Research on the teaching of RC in different social-scientific disciplines is limited [10], the existing literature claims the exposure to both qualitative and quantitative research methods in Social Sciences. For example, in the German educational system, the emphasis is on quantitative approaches, based on methodological textbooks [10]. Lettau & Breuer [53] considers that research teaching in psychology is oriented mainly on statistics and adheres to a hypothetico-deductive methodological framework. However, other researchers highlight the importance of qualitative methods in several areas of psychological research, such as Educational Psychology [53] and Psychotherapy research [54]. Böttcher & Thiel [6] proposed a new approach to RC development, across various academic disciplines, known as the RMRC-K-model. This model includes five elements: content knowledge, skills in reviewing the scientific literature, methodological skills, skills in interpreting research results and communication skills. Hence, in the articles reviewed, it was emphasised that RC should not be taken in its strict sense; therefore, the methods for teaching and learning RC require practising them through complex, challenging and ‘authentic’ activities. RC is developed in a problem-oriented environment, within a ‘hands-on’ approach. Marz et al. [1] developed a framework of RC, in which each skill is assigned to one of the three dimensions of RC: ‘generic’, ‘using research’, and ‘doing research’. The difference in the higher education program, pursued by master’s students, is relevant especially with regards to the research methodological approach followed by the school. Psychology students show stronger skills in applying quantitative methods, in comparison to students from other Social Sciences (Education, Political Sciences) that manage better qualitative methods [35]. This variance is explained by the focus of the curriculum of teaching research from those scientific fields [35] while the components of RC are largely interdisciplinary, there are differences between subjects depending on whether the focus is on quantitative or qualitative research methods.

What are the dimensions commonly used to assess the research competence of master’s students (Research Question 3)?

To answer our third research question, what are the dimensions commonly used to assess the RC of master’s students, we coded the articles content based on the input regarding how the relevant knowledge and skills to the cognitive and activity-based components of RC are assessed. Burke et al. [47] argue that there are specific assessment mechanisms for the achievement of RC across academic programs. The main instruments used were self-assessment questionnaires that helped teachers to identify the level of RC in terms of research knowledge and skills. Thus, the effectiveness of the course that aimed to form and develop this type of competence in the scientific sphere could be assessed. Students should be guided to conduct independent research [9]. Findings [47] report a low level of engagement and enthusiasm regarding research courses and a low interest in engaging in further graduate studies that would imply a strong research component. Teaching research is shifting from the traditional approach based on didactic research courses towards a strong emphasis on the development of scientific reasoning that starts with quality development of teacher education [55,56,57,58]. Evaluation of RC achievement for master’s students is carried out during research methodology courses, and throughout the process of master’s thesis writing. First, the expected research competencies should be identified for each level or academic year within each program. Based on these findings, recommendations on how to modify the curriculum could be applied to support students’ learning and development of the skills necessary to research process. Afterwards, during the whole process of teaching research, faculty should be able to obtain indicators of how the learning process is going. Some evaluation methods and tools identified in this review vary from performance on capstone projects, comprehensive examinations, and master’s thesis. The master’s thesis is a good indicator of a student’s success in developing RC. Master’s-level programs provide educational opportunities to continue professional development to students with different educational and experiential backgrounds, making it challenging for faculty to guide students to achieve the same level of RC [47]. This review is questioning if strict definitions for measuring competencies are useful at all, because competences arise various challenges in measuring them, as they should be performed in a new context. One might ask if there is a difference in RC outcomes of students that were studying engineering and students from other majors. A study [5] carried out aiming to test this hypothesis revealed little variation across the entire 4 years of undergraduate education, regardless of which major or university students enrolled.

5. Conclusions

This study used a SCR to investigate RC development among master’s students enrolled in Social and Engineering Sciences. The modelling of RC, during master’s programs in Engineering and Social Sciences, was explored to facilitate a research-based pedagogy program that can aid faculty to guide students in becoming researchers and applying research into their professional life, by taking evidence-based decisions. It is obvious that the research concept is complex and the process of developing it is challenging and is evolving dynamically in close relation to technology and the rapid changes in society RC is defined and developed differently in Social and Engineering Sciences in accordance with future perspectives and trends of specific study domains. Studies [7] suggest that active learning and research experience can foster student attitudes towards being more research-minded and, at the same time, they can increase scientific progress. Even though, Social Sciences and Engineering Sciences are quite distinctive scientific domains, and the review revealed some common aspects with regards to RC modelling, based on specific key skills that students are supposed to master, such as “scientific reasoning (including hypothetical-deductive reasoning, control of variables, proportional, correlation, and probabilistic reasoning)” [5] (p. 632), knowledge skills, technical skills and practices, abilities to understand the research philosophy, motivation and appropriate attitudes towards science. When it comes to research teaching in Social and Engineering Sciences, there is little difference, mostly in the amount of time spent in order to develop a specific skill from the RC. Studies [5] show little variation across program studies in scientific reasoning development, even though the general perception is that STEM or STEM-related fields are more likely to develop higher levels of reasoning skills throughout higher education. The structure of the study program should scaffold students’ potential academic success and research competence [59]. However, studies identified the assessing process of RC quite challenging as this SCR draws our attention on the complex process of RC development, as a long process requiring practice and activities implemented throughout higher education, regardless of the scientific field. RC strengthens learning-readiness and job-readiness in higher education [60]. This literature review shows, on the one hand the largely interdisciplinary nature of the RC, and on the other hand some differences in discipline-related specific skills, depending on the methodological focus and the knowledge content of a specific area of study. Further detailed scientific literature reviews are needed to be conducted to identify a research pattern on teaching [61], to enhance effective student engagement and experience [62,63], and to improve educational and research opportunities for master’s students [64].

This SCR identified existing gaps in literature that can be still investigated when it comes to teaching research at master’s level in both Engineering and Social Sciences. More comparative studies can be conducted in future to contribute to the development of a more coherent framework of teaching research and building RC. Furthermore, knowledge transfer and teaching experiences across various disciplines might generate innovative further competence-oriented higher education programs.

6. Limitations of the Study

Our review used only research articles in scientific papers, while for research modelling some other relevant policy documents, strategies and curriculum had not been analyzed. At the same time, little comparative data were identified on how RC is developed during master’s studies in on Engineering and Social Sciences. This is due to the fact that it was difficult to identify studies on how RC is taught and developed during Engineering Studies, which might suggest the challenge faculty meet when it comes to teaching research and metanalysis of this teaching-learning process.