Strengthening the ties between theory and practice in higher education: an investigation into different levels of authenticity and processes of re- and de-contextualisation

ABSTRACT

Although many attempts have been made to clarify how academic knowledge can be used in practice, there are not many empirical results that shed light on the process of developing academic knowledge from practical experience. The aim of this study is to examine to what extent an authentic learning environment supports master students in both processes of re and de-contextualisation. We used a qualitative and quantitative research method to evaluate the impact of learning environments that differed on the level of authenticity (less and more authentic). Participants described both learning environments as being instructive and realistic. We found strong correlations between motivation for learning, perception of authenticity and perception of experiential learning. Results suggest that more authenticity seems to (1) facilitate experiential learning, and (2) strengthen the ties between theory and practical learning experience. Additional implications for including reflective and collaborative elements to further support learning are discussed.

KEYWORDS:

• Authenticity
• experiential learning
• re-contextualisation
• de-contextualisation
• higher education

1. Introduction

For teachers and various educational professionals, lifelong learning is considered important for improving knowledge and career advancement (OECD 2019). Westbury et al. (2005) emphasise that in educational and professional programmes theoretically and practically oriented courses are intertwined. The perspective on the learning process over time might influence the division between educational ‘theory’ and ‘practice’ (Cochran-Smith and Lytle 1999; Oonk 2009; Stenberg, Rajala, and Hilppo 2016; Westbury et al. 2005). A series of articles studied this dichotomous approach in, for instance academic and reflective theory (Smith 1992), public and personal theory (Eraut 1995), knowledge-for-practice and knowledge-in-practice (Cochran-Smith and Lytle 1999), academic and practical knowledge (Even 1999), and practical judgement’ and epistemic theory (Korthagen and Kessels 1999). To this issue, Hegender (2010, 151) adds that knowledge can be described as propositional (‘knowledge that exist regardless of direct contact with a specific situation’) and procedural (‘knowledge that can only be expressed through procedures in a certain context with a clear intention to handle a specific situation’).

The effect of constructivist and social-constructivist thinking caused ‘a shift from a division between educational theory and practice to a view of theory and practice that exist in a dialectic relation’ (Orland-Barak and Yinon 2007, 957). Moreover, the dual ties between theory and practice become recognised as important for any contemporary higher education programme and research initiative (Leinhardt, McCarthy Young, and Merriman 1995; Oonk 2009). Leinhardt, McCarthy Young, and Merriman (1995, 404) acknowledge that the development in both directions (from theory to practice, but also from practice to theory) is necessary: ‘We have proposed that university [ies] should take on the task of helping learners integrate and transform their knowledge by theorising practice and practicing theory’.

1.1. Experiential learning

Recent efforts to provide learners with both practice experience and theoretical knowledge, often mentioned the concept of experiential learning (Kreber 2001; Larsen et al. 2017; Roberts 2018). Building on the works of twentieth century noteworthy scholars, Kolb (1984, 2015) stated that learning is the process of four cyclic steps: concrete experience (CE), reflective observation (RO), abstract conceptualisation (AC) and active experimentation (AE). In this way, learners get the opportunity to apply knowledge to a new experiences (re-contextualising knowledge, AE, CE). At the same time, new knowledge can arise from gaining concrete learning experience and be converted into abstract generalisations (de-contextualising knowledge, RO, AC) (Hennissen, Beckers, and Moerkerke 2017), but also from applying this new generic knowledge in other learning experiences (re-contextualising knowledge, AE, CE) (Lindsey and Berger 2009; Orland-Barak and Yinon 2007). This process represents a learning cycle where the learner may begin at any stage, but must follow each the sequence of four steps (experiencing, reflecting, thinking, and acting). Holman, Pavlica, and Thorpe (1997) and Tynjälä, Välimaa, and Sarja (2003) stressed that this way learners will achieve deeper and more meaningful understanding.

According to many researches, authenticity forms the core of pedagogic approaches that stimulate relations between concrete learning experience and knowledge (Ashford-Rowe, Herrington, and Brown 2014; Gulikers, Bastiaens, and Kirschner 2004; Lautenbach 2014; Villarroel et al. 2018). This is further confirmed by a review study by Radović et al. (submitted 2019a) that found elements of authenticity to be essential for designing experiential learning environments. Authenticity in learning is defined by the extent to which professional situations and context are reassembled in the learning environment (Ainsworth et al. 2012; Gulikers, Bastiaens, and Kirschner 2004, 2008; Newmann, Secada, and Wehlage 1995; Roach, Tilley, and Mitchell 2018). This may include a physical or virtual environment with all complexity and limitations of professional context (Gulikers, Bastiaens, and Kirschner 2004; Reeves, Herrington, and Oliver 2002). However, authentic learning happens when learners use professional tools, knowledge and skills, when imitate behaviour of experts and develop relevant outputs. Gulikers, Bastiaens, and Kirschner (2004, 2008) discuss five dimensions of authenticity that need to be reflected in the learning environment, namely (1) the task that resembles the complex inquiry; (2) the physical context that reflects the way knowledge, skills, and attitudes will be used in professional practice; (3) the social context that considers social processes that are present in real-life contexts; (4) the assessment that involves multiple indicators of learning; and (5) the criteria based on standards used in the real-life situation.

While authenticity provides students with real-world resources and professional tools, it can also support students to develop knowledge by generalising professional situations. In that respect, Radović et al. (submitted 2019b) point out elements of authenticity that need to be considered when designing learning that facilitates processes of re- and de-contextualisation. Their mARC instructional model (more Authentic, Reflective, and Collaborative) suggests that the design of authentic learning should include: (1) tasks with a high interdependence between theoretical inquiry and concrete learning experiences (reflecting the complexity of professional situations); to (2) demonstrate skills and knowledge by creating a significant product and build understanding; over (3) a sustained period of time; to support (4) the variability of experiential learning activities without rigidness of the fixed learning patterns; in order to (5) elicit higher order thinking and stimulate a wide range of cognitive strategies (including elaboration, analysis, organisation or deduction). While authentic tasks need to be complex enough to challenge learners, the learning process furthermore should include: (6) shared work and collaboration activities with peers and community of practice, to mimic activities of experts and professionals; (7) theoretical knowledge as a tool to understand a concrete learning experience (re-contextualisation); and should ensure that (8) students engage in generalisation processes in order to associate meaning from experience with a broader context of knowledge (de-contextualisation). By further explaining these guidelines, Radović et al. (submitted 2019b) stress the importance of strengthening the ties between theory-based courses and practice learning experience.

1.2. The pearls and perils of authenticity

Over the past years, numerous studies revealed the benefits of authenticity. They report that authentic learning maximises student engagement (Herrington and Kervin 2007; Larsen et al. 2017), motivation for learning and feelings of being prepared for future profession (Gulikers et al. 2008; Villarroel et al. 2018). However, engagement occurs if the students see the relevance beyond their learning activities (Herrington and Kervin 2007; Lautenbach 2014). Another benefit described is that students report enhanced self-efficacy and feelings of enjoyment (Aiken & Day 1999; Hursen 2016). Finally, authentic learning tasks foster students to grow and develop their knowledge, skills, and critical thinking (Herrington and Oliver 2000; Hramiak, Boulton, and Irwin 2009).

However, designing authentic learning environments presents certain challenges (Villarroel et al. 2018). There are several perils which may hinder integrating professional situations and fail to use (teach) experts skills within a formal higher education setting (Ashford-Rowe, Herrington, and Brown 2014; Lautenbach 2014; Strobel, Wang, and Dyehouse 2012). Gulikers, Bastiaens, and Kirschner (2004, 2008) and De Bruyckere (2017) assert that authenticity is a subjective concept, placed in the eye of the beholder. Empirical research has shown that it could be difficult for learners to structure experience and focus on developing understanding (Leijen et al. 2014) and outputs relevant for a professional community (Strobel, Wang, and Dyehouse 2012). Similarly, hindrances occurred when programs did not provide ‘real’ experiences (Aiken and Day 1999; Larsen et al. 2017; Lautenbach 2014) or when students perceive learning as being too time and energy consuming (Hramiak, Boulton, and Irwin 2009). The challenging aspects of authenticity are also reflected in the fact that the effects of authenticity depends on the way the learning process is designed (Radović et al., submitted 2019a).

2. Research questions for this study

The research reported here departs from two key postulates when designing authentic learning environments, and considers all the ‘pearls and perils’ of authenticity. The first postulate is that aligning the learning task with the professional proximity can be done based on Gulikers, Bastiaens, and Kirschner’s (2004) five-dimensional framework. The second postulate is that instructional elements of authenticity, distilled from the mARC model, can be used to enhance both processes of re- and de-contextualisation within experiential learning (Radović et al., submitted 2019a). Both the framework of Gulikers, Bastiaens, and Kirschner (2004) and the mARC model of Radović et al. (submitted 2019b) argue that authenticity can be seen as a continuum and not as a dichotomy.

This implies that learning environments can be less or more authentic. Therefore, to improve our understanding of what the concept of authenticity entails in academic settings, and how it relates to the concept of experiential learning, a study was set up compare learning environments in which authenticity was implemented differently (a less and more authentic learning environment). Four research questions were addressed:

1. Are different levels of authenticity related to academic performance?

2. Are different levels of authenticity related to motivation, enjoyment, perceived competences and usefulness, and perception of authenticity?

3. Are different levels of authenticity related to students engagement into re- contextualisation (AE & CE) and de-contextualisation (RO & AC)?

4. Are various demographic characteristics related to motivation, perception of authenticity, experiential learning and academic performance?

3. Method

To investigate our research questions, we used triangulation of both quantitative and qualitative research methods with respective statistical techniques. A less and more authentic learning environments were designed (to be further explained in 3.3 Context of the study) and participants could choose one of the designs. Multiple data sources were used: course academic report assessment as a measure of academic performance; a post-test questionnaire with measures on motivation, perception of authenticity and experiential learning; and debriefing activities to get more qualitative insight in the learning process and opinions of participants. Ethical approval for this study was granted by the Ethics Review Committee of the Open University of the Netherlands.

3.1. Participants

The study was situated in the first of three core courses of a distance learning Master of Educational Sciences program. The program is designed for professionals in education, mainly teachers who seek an academic masters’ degree and combine work and study to attain this goal.

Participants of this study were students of one cohort who completed the course on time and gave written consent to participate in the study (n = 37). Table 1 provides a comprehensive picture of the demographics collected with a questionnaire (six students did not fill in the questionnaire). Participants were divided into two groups based on their choice, further specified as LA (Less Authentic condition) and MA (More Authentic condition) groups as the learning task differed in the extent of authenticity incorporated in course design

Table 1. Students’ demographic information.

Category	LA (n = 19)		MA (n = 12)		Total (n = 31)
	n	%	n	%	n	%
Gender
Male	1	5%	3	25%	4	13%
Female	18	95%	9	75%	27	87%
Previous level of Education
Professional bachelor/master	11	58%	11	92%	22	71%
University bachelor/master	8	42%	1	8%	9	29%
Experience in professional work
0–5 years	5	26%	2	17%	7	23%
5–10 years	4	21%	2	17%	6	19%
>10 years	10	53%	8	66%	18	58%
Expertise during professional work
Teaching professional background	13	68%	7	58%	20	65%
Age	M	SD	M	SD	M	SD
In years	35.05	8.32	40.83	9.40	37.3	9.19

Note: LA, Less Authentic group; MA, More Authentic group; M, Mean; SD, Standard deviation.

3.2. Measuring instruments

3.2.1. Academic performance

Effect on academic performance is measured through course assessment of students’ final assignment (writing an academic report). Course criteria assess the extent students apply theory to practice and the extent they extract and report theoretically relevant meanings from a situation in practice. It includes three segments: (a) the quality of reported research (seven criteria); (b) the quality of demonstrated theoretical knowledge (four criteria); and (c) academic writing (four criteria). A sum formed the final grade. Scoring was conducted by one teacher after five teachers had calibration sessions on the first three papers.

3.2.2. The questionnaire

Based on the research questions, a questionnaire made of 42 items was constructed (items rated on a seven-point Likert scale, ranging from one (totally disagree) to seven (totally agree)). The questionnaire combined subscales from Ryan and Deci’s (2000) the Intrinsic Motivation Inventory (IMI), Gulikers, Bastiaens, and Kirschner’s (2004) 5D framework for authenticity (5DF), and Young, Caudill, and Murphy’s (2008) instrument for experiential learning (EXP). Additional items were used to collect learner’s demographic information (Age, Previous level of Education, Experience in professional work, and Expertise during professional work).

From the seven IMI dimensions, we used three subscales (in total 20 items): ‘Interest/ Enjoyment’ (IMI.IE, seven items) – perception of interest and enjoyment; ‘Perceived Competence’ (IMI.PC, six items) – perception of performance and acquired competences; and ‘Value/usefulness’ (IMI.VU, seven items) – perception of benefits from the activity. The IMI has been used widely in studies on motivation (e.g. Jansen in de Wal et al. 2014; Klaeijsen, Vermeulen, and Martens 2018). Ten items from the 5D framework were included with following dimensions: ‘Course authenticity’ (5DF.CA, three items) – perception of course authenticity; ‘Task Authenticity’ (5DF.TA, three items) – perception of whether the task resembled the real-world activities; and ‘Physical context’ (5DF.PC, four items) – perception of whether the context of performing task was realistic. Finally, the complete questionnaire from Young, Caudill, and Murphy (2008) was used (total 12 items) to measure the quality of experiential learning. This questionnaire has four dimensions (each contains three items) that estimate learners’ awareness of Active Experimentation (EXP.AE) and Concrete Experience (EXP.CE), as two steps of Re-Contextualisation; as well as Reflective Observation (EXP.RO) and Abstract Conceptualisation (EXP.AC), as two steps of De-Contextualisation.

3.2.3. The debriefing session

To gain deeper insights into students’ activities and experiences while performing course tasks quantitative data were supplemented with qualitative data obtained from semi-structured debriefing session. The debriefing session with students contained a student reflection on the learning process stimulated by four open questions (the full list of questions for debriefing is given in Appendix 1).

3.3. Context of study

The course we studied was designed as a hands-on introduction in educational research and instructional design for practitioners with educational background. Eight principles of the mARC model (introduced in the last paragraph of Section 1.2) were lined with the course design to facilitate both processes of re- and de-contextualisation within experiential learning. The course enabled students to study literature (AE), conduct an observational study of a classroom learning situation (CE), analyze a classroom learning situation from the theoretical perspective and with the tools of an educational researcher (RO), and at the end to make generalisations from the concrete experiences through the lens of theory and methodology (AC) when writing an academic report (seventh and eight principle of mARC).

Furthermore, by doing practical case-study research, students should develop insights in the application of learning theories and principles at micro level (in classroom) and at meso level (curriculum design) (first principle of mARC). During the period of 11 weeks students are guided towards task completion through a series of learning activities (third principle of mARC). Students work individually or in groups, by studying material on learning theories, course and curriculum design, case design methodology, organising, and on conducting research and reporting studies (fourth and fifth principle of mARC). They are encouraged to design materials to analyses data in collaboration. Oral reporting takes place in online poster presentations and group discussions, where written reporting is done individually (sixth principle of mARC). The course starts with a face to face introduction and continues online. Students and teachers interact through discussion boards and regular synchronous meetings in the Virtual classroom (Collaborate software). In the last week students complete the course by submitting written academic report for assessment (second principle of mARC). See Appendix 2 for more details on the alignment of course design and eight principles for authenticity of mARC implemented to facilitate both processes of re- and de-contextualisation within experiential learning.

For this study, the course was implemented in two variants that differed in the way authenticity of the learning environment was conceptualised. Table 2 demonstrates the differences from the authenticity perspective (on three of five 5DF dimensions, with Assessment and Criteria being the same for both conditions).

Table 2. Authenticity of the learning environment as conceptualised in the present study based on framework by Gulikers, Bastiaens, and Kirschner (2004).

Authentic Dimension	As conceptualised in the course	In less authentic condition (LA)	In more authentic condition (LA)
Task authenticity	Conducting an observational study in the educational practice at micro level (one lesson observation) and at meso level (documentation).	Observation of a video-recorded classroom situation and analysis of documents, all available online. Level of dimension: medium.	The students need to organise and conduct observation study in a real school context. Level of dimension: high.
Social context	Social processes that are equivalent to those in a professional context of a researcher included making arrangements with the teacher, principal, relevant others from a school.	Social context of a professional practice was lacking as students were provided with all materials. Therefore, the aspect of social context was missing. Level of dimension: low.	Students contact a school, communicate with involved teachers and school team, and execute the interview with teacher. Level of dimension: high.
Physical context	The physical context reflects the availability and variety of professional resources, the time constrain, as well as the complexity of professional situations presented in a research situation and online conference.	This aspect was limited, as student were offered a video recording of a learning situation and a set of accompanying documents. Level of dimension: low.	There was availability and variety of professional resources. It include school premises with all complexity and variety of research resources. Level of dimension: high.
Overall level of authenticity		Less Authentic	More Authentic

While MA students had freedom to choose a classroom learning situation to observe, who and how to conduct interviews, and which school documents to analyze, LA students were offered pre-selected observation, interview, and materials. As a consequence, the dimension of ‘task authenticity’ for tasks the learner had to carry were different. Furthermore, the dimension of ‘physical context’ varied between two variants of the course because of (a) dissimilarity to work environment (e.g. organising research and collection data in real practice), (b) availability of resources (e.g. a variety of resources, being able to choose the set of documents, or chose the set of literature), and (c) differences regarding time constraints and limits (Gulikers, Bastiaens, and Kirschner 2004). Aspects of ‘social context’ also differed between LA and MA, as a direct consequence of different social interactions (organising observations, making arrangements with people in charge of affairs, and planning interviews), and a positive interdependence on the members of the school and the teacher. Also, students in MA had more opportunities to use learning results outside the learning environment (e.g. the theoretical framework is used in real classroom settings) (Strobel, Wang, and Dyehouse 2012).

Constrained by the educational vision, rules of examination and ethical issues of our university, we were not in a position to make a greater difference, therefore the last two dimensions of authenticity (results and criteria) were the same in LA and MA. Students are expected to demonstrate a certain level of performance as researchers by conducting a study, presenting it orally and writing it up. The authentic character of the results is reflected in the variety of professional skills students develop and multiple indicators of work (developing an instrument based on theoretical assumptions, creating a poster, giving an oral presentation during a virtual conference, and writing an academic report).

Finally, the course ‘criteria’ were used to assess the academic reports of the studies performed (with a maximum of 3000 words). Students were expected to demonstrate knowledge of learning and instructional theories, to clearly describe the observational case study, to carry out a structured and comprehensible data analysis, and to link results to theoretical principles. Teachers explained these criteria in the learning environment and the virtual class sessions. These criteria are similar for the evaluation of work in professional situations, like for journal or conference paper reviews. Academic reports must meet the requirements of scientific reporting (e.g. the overall structure to be included in an academic report), the content of the report (e.g. how students apply theory to practice, and how they extract, describe, and report theoretically relevant meanings from a practical situation), and academic writing (e.g. the quality of argumentation and use of language).

4. Results

The internal consistency of each subscale of the questionnaire was calculated using Cronbach's α statistics (Taber 2018). By looking in Table 3, four dimensions (with low numbers of items) were reliable with α values between .58 and .7, two dimensions had adequate reliability above .7 and four dimensions had high reliability above .8. As indicated in earlier works (Cho and Kim 2015; Taber 2018), scores that have a low number of items associated with them, as well as non-normally distributed data, tend to have lower reliability. Thus, subscales achieved sufficient internal consistency.

Table 3. Cronbach’s α and Spearman’s rank-order correlations (n = 31).

Subscales of questionnaire	IMI.IE	IMI.PC	IMI.VU	5DF.CA	5DF.TA	5DF.PC	EXP.CE	EXP.RO	EXP.AC	EXP.AE
Interest/Enjoyment (IMI.IE)	1
Perceived competence (IMI.PC)	ns	1
Value/Usefulness (IMI.VU)	.75**	ns	1
Course authenticity (5DF.CA)	ns	.37*	.41*	1
Task Authenticity (5DF.TA)	ns	.48**	ns	.52**	1
Physical context (5DF.PC)	.47**	ns	.37*	ns	ns	1
Concrete experience (EXP.CE)	.55**	ns	.59**	ns	ns	.60**	1
Reflective observation (EXP.RO)	.53**	ns	.53**	ns	ns	.67**	.69**	1
Abstract conceptualisation (EXP.AC)	.65**	ns	.79**	.40*	ns	ns	.56**	.48**	1
Active experimentation (EXP.AE)	.63**	ns	.69**	.38*	ns	.55**	.76**	.53**	.54**	1
N (numbers of items)	7	6	7	3	3	4	3	3	3	3
Cronbach’s α	.95	.84	.87	.84	.58	.63	.62	.71	.76	.62

Notes: *Correlation is significant at the 0.05 level (2-tailed). **Correlation is significant at the 0.01 level (2-tailed). IMI = constructs correspond to the motivation subscale, 5DF = constructs correspond to the authenticity subscale, EXP = constructs correspond to the experiential learning subscale.

As much of the data were not normal non-parametric tests were run. To determine the correlation among subscales of motivation, authenticity and experiential learning in the questionnaire, Spearman rank-order correlation was run (Green and Salkind 2008). Mann–Whitney U-tests were used to investigate whether there was a statistically significant difference in the dependent variable for two groups (McElduff et al. 2010). First, we analysed whether the academic performance was the same for students from LA and MA groups. Second, we tested for differences of dimensions of motivation, authenticity and experiential learning, with respect to the two groups. Later, we analysed the effects of within-subjects measures of Age, Education, Experience, and Expertise on the final grade and each dimension of motivation, authenticity and experiential learning.

4.1. Correlation analysis of questionnaire dimensions

A Spearman’s rank-order correlation was run to determine the relationship between the subscales of the questionnaire. Our analysis suggests that 26 correlations between subscales of the questionnaire were statistically significant. The results of the complete correlation analysis are presented in Table 3. Furthermore, a test of significance indicated that there was a strong and positive correlation between overall subscale of motivation (IMI), authenticity (5DF) and experiential learning (EXP). Increases of overall motivation were correlated with increases of overall perception of authenticity r_s(29) = .61, p < .01, and overall experiential learning r_s(29) = .73, p < .01. Finally, the higher students’ perceived the overall authenticity, the more they were able to engage with experiential learning r_s(29) = .54, p < .01.

4.2. Academic performance

The Mann–Whitney U-test revealed no significant effect of level of authenticity on the academic performance, although we see tendency that participants in MA group scored higher than participants in the LA group on each of the evaluation criteria (Table 4).

Table 4. The learning effects on the academic performance of participants in LA and MA groups.

Evaluation criteria & Grades	Mean ranks		Mann–Whitney
	LA	MA	U score	z-score	P-value
1. Scientific reporting	16.55	19.72	124.5	−.918	.359
2. Content of the report	16.92	19.28	131.5	−.684	.494
3. Academic writing	15.16	21.38	98	−1.8	.072
Cumulative assessment	16.42	19.88	122	−.994	.320
Final Grade	16.18	20.16	117.5	−1.181	.238

Note: LA, Less Authentic group; MA, More Authentic group.

The Mann–Whitney U-tests were repeated for within-subjects measures of Age, Education, Experience and Expertise. The results of the additional analysis showed that academic performance of older students was significantly higher than performance of younger students (U = 39, p = .047). It can also be concluded, that the final grades of students with more experience were significantly higher than the final grades of the less work experienced students (U = 30, p = .031). Furthermore, there were no effects of education or expertise on the final grade (Table 5).

Table 5. Analysis of the relation between demographic characteristics and academic performance measured with Final grade.

Significance effect*	Mean Ranks		Mann–Whitney
			U score	z-score	P-value
Age	YO = 9.57	OL = 16.73	39	−1.99	.047
Education	HBO = 13.30	WO = 18.78	56	−1.647	.100
Experience	LE = 8.50	ME = 16.70	30	−2.158	.031
Expertise	T = 14.21	NT = 16.50	80	−.707	.479

Note: YO (n = 7) = students younger than 30 years; OL (n = 22) = students older than 30 years.

HBO (n = 20) = students from universities of applied science; WO (n = 9) = students from research universities.

LE (n = 6) = students with less than 5 years of working experience; ME (n = 23) = with more than 5 years.

T (n = 19) = students with teaching experience; NT (n = 10) = students without teaching experience.

4.3. Differences in rating of motivation, authenticity and experiential learning

Table 6 illustrates the means and standard deviations of motivation, perceptions of authenticity and experiential learning between LA and MA group. The higher ranking of all subscales was on face value present in MA group (when compared to LA group). To evaluate whether these differences were statistically significant, the Mann–Whitney U-tests were used (Table 7).

Table 6. Means and standard deviations of each subscale of the questionnaire.

Subscales of questionnaire	Less Authentic (n = 19)		More Authentic (n = 12)
	M	SD	M	SD
Interest/Enjoyment (IMI.IE)	5.32	1.05	5.74	.77
Perceived competence (IMI.PC)	4.89	.68	5.01	.68
Value/Usefulness (IMI.VU)	5.90	.78	6.07	.43
Course authenticity (5DF.CA)	5.33	1.08	5.56	.69
Task authenticity (5DF.TA)	4.68	.77	5.08	.68
Physical context (5DF.PC)	5.32	.71	6.10	.60
Concrete experience (EXP.CE)	5.65	.55	6.03	.44
Reflective observation (EXP.RO)	5.40	.94	5.94	.65
Abstract conceptualisation (EXP.AC)	6.07	.62	6.17	.39
Active experimentation (EXP.AE)	5.44	.79	5.94	.40

Note: M = Mean (from 1 to 7); SD = Standard deviation; IMI = constructs correspond to the motivation subscale, 5DF = constructs correspond to the authenticity subscale, EXP = constructs of correspond to the experiential learning subscale.

Table 7. Effects of authenticity on motivation, perceptions of authenticity and experiential learning.

Questionnaire constructs	Subscales	Mean Ranks		Mann–Whitney
		LA	MA	U score	z-score	P-value
Motivation	Interest/Enjoyment (IMI.IE)	14.79	17.92	91	−.936	.349
	Perceived competence (IMI.PC)	15.37	17.00	102	−.490	.624
	Value/Usefulness (IMI.VU)	16.00	16.00	114	0	1
	Motivation overall	14.87	17.79	92.5	−.874	.382
Authenticity	Course authenticity (5DF.CA)	15.47	16.83	104	−.416	.677
	Task authenticity (5DF.TA)	14.16	18.92	79	−1.443	.149
	Physical context (5DF.PC)	12.03	22.29	38.5	−3.083	.002
	Authenticity overall	12.89	20.92	55	−2.401	.016
Experiential learning	Active experimentation (EXP.AE)	13.50	19.96	68.5	−1.878	.060
	Concrete experience (EXP.CE)	13.82	19.46	66.5	−2.081	.037
	Re-Contextualisation	13.26	20.33	62	−2.13	.033
	Reflective observation (EXP.RO)	15.74	16.42	72.5	−1.729	.084
	Abstract conceptualisation (EXP.AC)	13.61	19.79	109	−.209	.835
	De-contextualisation	14.32	18.67	82	−1.313	.189
	Experiential learning overall	13.74	19.58	71	−1.747	.081

Note: LA (n = 19) = Less Authentic group; MA (n = 12) = More Authentic group.

The analysis of data shows no significant differences between MA and LA groups regarding motivation (and its subscales). By contrast, perception of overall authenticity was significantly higher in MA than in LA group (U = 55, p = .016). Moreover, students in MA perceived that context (5DF.PC) in which they had to perform was realistic and looked like professional practice (U = 38.5, p = .002) significantly more often than students in LA. There was no difference regarding rating of the other two subscales: the course was oriented toward future profession (5DF.CA) and the task looked similar to the task of real researcher (5DF.TA).

Regarding overall perception of experiential learning, the Mann–Whitney U-test demonstrated a tendency for students to perceive their learning environment as more experiential (U = 71, p = .081) if the environment encompasses more authenticity. Next, it can be concluded that more authenticity in the learning environment influenced students to rate the re-contextualisation process significantly higher than students in the less authentic environment (U = 62, p = .033). More authenticity in the learning environments had a significant effect on the perception that (1) new learning experiences or professional situations were encountered (CE, U = 66.5, p = .037) and that (2) experimenting with course concept and theories was done in order to improve understanding (AE, U = 68.5, p = .06).

On the contrary, there was no statistical effect of different levels of authenticity found on the de-contextualisation process of experiential learning. Although, this can be the consequence of the ‘ceiling effect’, as both LA and MA students scored very high. That becomes evident from Table 6, where Means (Standard deviation) regarding the sub-construct of AC were 6.07 (.62) for LA, and 6.17 (.39) for MA students.

Finally, The Mann–Whitney U-test was repeated for within-subjects measures of Age, Performance, Education, Experience and Expertise for each of the dependent variable (Motivation, Authenticity, and Experiential learning). These variables had no significant effect on the perception of authenticity and experiential learning. The only significant statistical difference was in favour of participants coming from the research universities, when compared to students coming from universities of applied sciences, regarding the perception of the value and usefulness of learning activities (U = 51.5, p = .038).

4.4. Analysis of the debriefing sessions

Examples of the students’ responses during the debriefing session are included to provide more clarity on the overall perception of the learning processes and the awareness of re- and de-contextualisation processes. Students in both groups agreed on the relevance of authenticity, and clearly value the contextualisation of learning in a context that mirrors professional work. Moreover, no negative observations were noted.

The assignment was instructive and especially interesting because you get a feel for the theory, learn to recognize the concepts in a real situation and also learn to write an academic report. All concepts are present and you are given many tools to work with the (many) theory and to organize it in such a way that it becomes logical (Student 13, LA).

The task was interesting in terms of content. Furthermore, the performance in a realistic setting was instructive (Student 25, MA).

As described earlier, the learning task included a variety of assignments and activities in a context of professional practice. The most students, in both groups, claimed that they had opportunity to make a connection between knowledge and practical experience:

It is interesting to link theory to practice and practice to scientific writing. I still find this very difficult, so a good learning process (Student 8, LA).

I could combine the theory and my practical experience to carry out the assignment (Student 26, LA).

Although I have a lot of observation experience; yet from a larger learning-theoretical framework it was a new experience. It helps to try to connect practice and theory (Student 9, MA).

However, when students describe their awareness of ties between theory and practice, the process of re-contextualisation seems to occurs more often than pointing out processes of de-contextualisation. This aspect of placing theory into practice becomes more evident when analysing students debriefing:

The assignment was fun and instructive to do. It gave a picture of what an educationalist does to put the theory into practice (Student 17, LA).

It gives concepts depth and places them more in concrete reality (Student 25, MA).

Once the learning theory framework was constructed, I could easily recognize it and link it to the instructions (Student 4, MA).

5. Discussion and conclusion

Following the extensive literature of Brown, Collins, and Duguid (1989), Herrington and Oliver (2000), Gulikers, Bastiaens, and Kirschner (2004, 2008) and many others, students should be given the opportunity to apply knowledge in the context of the (future) work environment using professional skills and tools. Yet, the impact of such learning environments on experiential learning within academic master’s program remains largely unexplored. This study was set up to provide empirical evidence on how authenticity can be used to support motivation, academic performance and facilitate both re- and de-contextualisation of knowledge. Findings (both qualitative and quantitative) yield a number of important points for discussion.

Regarding the first research question, it should be noted the difference between the grades were not statistically significant. Our additional analysis shows that students in a more authentic environment perceived higher overall authenticity then students in a less authentic environment. This is in line with Strobel, Wang, and Dyehouse (2012) who suggested that mirroring professional context and output are important features of the perception of authenticity. Although the variance between the two learning environments in our study was only manifested in three of the five dimensions of the Gulikers, Bastiaens, and Kirschner’s (2004) framework, it seems that this was sufficient enough for students to perceive the difference in overall authenticity. This may be because the task and context dimensions of authenticity are the most obvious to observe (Strobel, Wang, and Dyehouse 2012). Roach, Tilley, and Mitchell (2018) suggested that these two dimensions together provide enough cognitive realism to ensure students’ authentic learning. Additionally, our study varied the social dimension of authenticity as students had an opportunity to contact a school, communicate with involved teachers and school team, collect material, and execute the interview with teacher. Therefore, students in MA (1) interacted with a professional community of practice, and (2) used learning outcomes outside the learning environment (e.g. the theoretical framework students create is used during real classroom observation). Strobel, Wang, and Dyehouse (2012) considered the latter as a critical factor of authenticity that motivates students to pursue a certain activity (Impact Authenticity).

Furthermore, we found that different students demographics (such as performance, age, education, work experience, and professional expertise) did not influence the students’ perception of authenticity. These results indicate that two levels of authenticity were designed in such way to be independent of students’ demographics. This resulted to some degree in answering the long standing issue about how to effectively persuade learners in higher education programs that they are learning in an authentic environment (Herrington et al., 2000; 2007). It can be concluded that aligning the learning task with the professional proximity can be successfully done based on Gulikers, Bastiaens, and Kirschner’s (2004). In addition, we propose educators to design authentic tasks according to all five dimensions of authenticity, and most importantly, to incorporate a higher level of authenticity in each of the dimensions.

With regard to the second research question, the results of the correlation analysis indicate a positive relationship between the dimensions of motivation (perceived interest and value), perception of authenticity and experiential learning. Moreover, the overall perceptions of motivation, authenticity and experiential learning were dependent on each other, interlinked rather than discrete and disconnected. These results are in line with Herrington and Oliver (2000) and Hramiak, Boulton, and Irwin (2009) who earlier concluded that authentic learning tasks help students to develop professional skills and to stay motivated for the learning process.

Regarding the third research question, whether students were able to engage in the steps of Kolb’s cycle, the research results are in favour of more authenticity. These results indicate that designing the authentic learning task to facilitate experiential learning (and both processes of re-contextualisation and de-contextualisation), can be successfully done following the eight principles of the mARC model (Radović et al., submitted 2019b), as introduced in the theoretical section of this article. Students in MA scored significantly higher than students in LA on the Re-Contextualisation sub-construct, indicating that more authenticity (1) gave them more practical experience to help construct theoretical concepts and (2) involved them in testing ideas and experimenting with the course concepts. No difference was found on the De-Contextualisation sub-construct. Two possible explanations exist for these findings. First, the Abstract conceptualisation step (EXP.AC) was rated equally and very high across two groups (see Table 6). Second, insights from the debriefing sessions indicated that students do not clearly generalise from these practical learning experiences. Our data suggest that students’ awareness of the re-contextualisation process seems to occur more often than awareness of processes of de-contextualisation. This could well be a specific characterisation of this specific group of participants, who are already working as professionals and have mainly experienced re-contextualisation practice in their previous education (within teacher education institutes where students practice theory, rather than theorise on practice). Following discussion will provide recommendations for future studies on this subject.

Finally, in the light of the fourth research question, we investigated the effects of different demographic factors. Our analysis has shown that the older participants performed better than the younger students. Moreover, students with more work experience performed significantly better than students with less work experience. One of the possible explanations for this, as Darling-Hammond and Snyder (2000) mention, is that students with more working experience are often more capable to relate authentic learning experience in such a way that new knowledge is created.

Two limitations of this study should be taken into account. First, constrained by the educational vision, rules of examination and ethical issues of our university, we were not in a position to make even greater difference between two authentic environments. Also, we were not able to compare these two authentic conditions with other environments, which followed a more traditional approach to university education (let’s say not-authentic). While various problems could occur (other than the non-comparable characteristics of content, different student populations, roles of teachers during learning, et cetera), we still believe that the results of such a comparison could be interesting. Second, our study presented results from a rather small sample of only 37 participants. Some of the results were on the edge of statistical significance, and it is possible that if more participants would have been involved, these results would have reached significance. Finally, a methodological issue regarding sampling should also be addressed. Students were free to choose a learning condition. They were aware of the ‘video option’ as a contrast to the ‘live observation’. For this study we were not able to investigate whether this bias the outcomes of the research.

Our discussion raised two interesting recommendations for future studies needed to be examined in particular. First, it must be emphasised that authentic environments in this study encompassed reflection learning processes, although this was not a dominant learning strategy used. According to Elvira et al. (2017) and others, reflection should be an important aspect of the learning process for students to develop higher order thinking skills, and an ability to generalise from learning experience and rationalise decisions made in regard to the developed understanding and previous beliefs. Boud, Keogh, and Walker (1985, 19) wrote that reflection does not happen alone, rather learners must be supported to ‘explore their experiences in order to lead to new understanding’. Moreover, the lack of critical reflection on the relevant learning experiences can hinder the process of developing understanding and generalisation form practical experience. Following these conclusions and according to our results, future research should investigate to what extent critical reflection activities can be included to further support students generalisation and abstracting; rather than just having a perception of engaging into process of de-contextualisation.

Second, this study asserts that older students, as well as students with extensive work experience, outperformed younger and less experienced students. More insights in the characteristics and mechanisms that provoke these outcomes can help design more effective learning environments. Perhaps designing more knowledge sharing activities (between more and less experienced students) could help students to engage with new ideas and different perspectives. A similar conclusion is indicated by a recent study by Clara et al. (2019), in which they explain that sharing reflective thinking between peers in a collaborative setting could promote more critical thinking. This leads to a final recommendation for future studies to investigate to what extent collaborative activities can be used to share expertise and professional knowledge when re- and de-contextualising in an authentic learning environments.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Appendix 1. The questions for debriefing session

Table

1. Looking back at the task that was central to this course, how can you characterise the task – when answering, you can indicate to what extent the task was (or not) interesting, instructive, fun to do and why.

2. Could you use your experiences to better understand (learning) theory concepts in performing this task – explain your answer!

3. Did you have sufficient opportunity during the course to reflect on learning about the task you were performing?

4. Did working with your fellow students help you learn in this course? What did you find positive and less positive about this collaboration.

Appendix 2. Details on the alignment of course design and eight principles for authenticity of mARC to facilitate both processes of re- and de-contextualisation within experiential learning

Table

mARC principles		Operationalised in the course design
1.	Develop task with a high interdependence between theoretical inquiry and concrete learning experiences (reflecting the complexity of professional situations)	The main task in the course facilitates learning experiences at a deeper level of reasoning by making the dependency between theoretical knowledge and practical learning experience (both in LA and MA). Students are expected to (1) study literature on educational theories, (2) conduct an observational study (in LA based on a video recording of learning situation; while in MA based on a real classroom learning situation), (3) analyse a classroom learning situation from the theoretical perspective and with the tools of an educational researcher, and at the end of the course (4) make generalisations from the concrete experiences through the lens of theory and methodology when writing a scientific essay.
2.	Make opportunities for students to demonstrate skills and knowledge by creating a significant product and creating understanding	By carrying out an observation study, both students in LA and MA are expected to apply learning theories and principles at micro level (in the classroom) and at meso level (curriculum design). Learning is embedded in a context that reflects the complexity of research (less authentic in LA, and more authentic in MA), to provide students with sufficient opportunities to (1) demonstrate knowledge (building research instrument based on knowledge of learning theories); (2) use professional skills (using research instruments during observation, interviewing and collecting documents (only in MA), analysing data, and presenting results), and (3) create relevant and significant learning products (poster for public presentation and an academic essay).
3.	Provide a sustained period of time for finishing task	For the period of 11 weeks, students are guided, throughout the series of learning milestones, to solve one complex task (doing an observation study). With different learning activities in each of the learning milestones, students are gradually introduced to theoretical knowledge and professional tools that are seamlessly integrated into the complexity of the overall task.
4.	Facilitate that students see the variability of experiential learning activities without rigidness of the fixed learning patterns	The course enables and encourages students to carry out an observation study, in which they mimic the work of researchers. The main task is ill-defined, from students is expected to outline the subtasks (decide research questions, produce research plan, chose education situation (only in MA), organise observation (only in MA), collect data, analyse data, prepare presentation, and write academic essay); and, only in MA, to plan additional activities such as: making agreements with an educational institution, prepare and objectively conduct observation. Students may use various resources to support their observation from a number of different viewpoints (although the set of documents is limited in LA).
5.	Task should elicit higher order thinking and stimulate a wide range of cognitive strategies (including elaboration, analysis, organisation or deduction)	To successfully accomplish the task, students need to use higher order thinking skills like elaboration, analysis, organisation and deduction. This is echoed in various learning activities, such as: (1) formulating research questions (significant from both a theoretical and a practical viewpoint); (2) longitudinal focus on the research question; (3) organising observation (only in MA); (4) developing assumptions, analysing data and constructing conclusions in respect to the research questions; (5) formulating conclusions for an academic essay; and finally (6) presenting arguments and discussing result during poster presentation.
6.	Task should include shared work and collaboration activities with peers and community of practice, to mimic activities of experts and professionals	The course starts with a face to face introduction of students and teachers, and continues online. Students work individually or in groups using an online web platform. Students are encouraged to work together to design their theoretical framework in order to analyses data. Another collaborative activity, online poster presentation, gives students the opportunity to share research results, express different points of view, and learn from discussion. Next, a written report is done individually. Only in MA, the task also includes a professional context of a researcher to mimic social activities when making arrangements and collaborating with the teacher and relevant others from an educational institution where their observation is planned.
7.	Theoretical knowledge should be used as a tool to understand a concrete learning experience (re-contextualisation)	The task requires students to design and develop an analytical framework to understand a classroom situation. The analytical framework is built upon the understanding of learning theories and requires the transfer of theoretical knowledge in the process of design. In addition, the assessment of the students is also determined by the extent and degree to which this analytical framework is used in practice.
8.	Students should be engaged in generalisation processes in order to associate meaning from experience with a broader context of knowledge (de-contextualisation)	The task involves students in the process of abstract conceptualisation. As a results, students develop and advance their theoretical knowledge (knowledge of concepts, facts, and learning theories) when (1) explaining their research results, and (2) drawing conclusions through reflective consideration of results. Furthermore students are supported to generalising various results during poster presentation session, and to construct knowledge based on results and ideas of others.

Note: LA, Less Authentic environment; MA, More Authentic environment.