Research article
Open Access

Design and practice of navigation-based learning (NBL) as a novel method for clinical thinking training

Yi-Zhou Wu[1], Jie Sun[2]

Institution: 1. Department of Cell Biology, School of Basic Medicine, Nanjing Medical University, 2. Safety Assessment and Research Center for Drug, Pesticide and Veterinary Drug of Jiangsu Province, School of Public Health, Nanjing Medical University
Corresponding Author: Prof Jie Sun ([email protected])
Categories: Curriculum Planning, Educational Strategies, Technology
Published Date: 09/09/2019


Objectives: In recent years, many medical universities in China have launched Problem-Based Learning (PBL) curriculum. It improves the autonomous learning ability, but also exposes some problems and shortcomings. For example, the low learning efficiency due to excessive freedom of atmosphere and insufficient guidance of tutor, the lack of clinical training due to case compiling and curriculum design, etc. To solve these problems, we conceive a new method Navigation-Based Learning (NBL) in this study.


Methods: A standard learning group includes one tutor and ten students. The NBL cases containing two acts are generated by expanding and modifying real clinical records. The learning process comprises a series of steps: Introduction (10 min), Act Ⅰ (75 min), Act Ⅱ (75 min), Summary (20 min). The learning quality is further evaluated by an objective examination and a subjective questionnaire, followed by quantitative analyses with various statistical models. 


Results: The results of examination show that NBL achieves similar learning quality as PBL. Benefiting from enhanced guidance and compressed course time, NBL reaches a higher learning efficiency than PBL. The results of questionnaire show that the approval rating of NBL is 85.11%. Compared with PBL, the high support rate of NBL is attributed to the advantages of four aspects, including learning efficiency of unit time (HR=1.119, p=0.029), clarified learning orientation (HR=1.093, p=0.039), authentic simulation of clinical diagnosis and treatment scenarios (HR=1.139, p=0.033), clinical thinking and logical reasoning (HR=1.089, p=0.033).


Conclusions: NBL has been proved to be an effective learning method in clinical thinking training for medical students. It achieves a balance between promoting efficiency and maintaining interest in medical learning.


Keywords: Navigation-based learning; Problem-based learning; Curriculum; Clinical scenario; Medical education


Education is not the filling of a pail, but the lighting of a fire. William Butler Yeats stressed the need for teachers to light the student’s fire by inspiring them to learn, explore and create. For beginners of clinical medicine, if learning starts with interest, the learners will devote a great deal of enthusiasm and vigor, which will naturally lead to higher learning efficiency and better outcomes. Modern medical knowledge covers a wide range from basic physiology, anatomy, pathology to clinic. It contains a large amount of detailed knowledges and complicated mechanisms, which are relatively abstract and difficult to master. If the interest of students cannot be effectively stimulated in the initial stage of learning, it is likely that there will be a phenomenon of "get half the results with double the effort". In this situation, Problem-Based Learning (PBL) was proposed. The PBL curriculum require students to discover problems independently, learn relevant knowledge, communicate and solve issues, and cultivate self-learning ability (Preeti, Ashish and Shriram, 2013; Ellaway, Poulton and Jivram, 2015; Orsmond and Zvauya, 2015; Torre, van der Vleuten and Dolmans, 2016).


Many universities in China launch PBL in recent years, however, several issues emerged in course implementation. For example, low learning efficiency due to the free and relaxed learning atmosphere and insufficient guidance, the lack of clinical simulation in case conception, and the lack of clinical thinking training, etc. (Fan et al., 2014; Sun, Chen and Wu, 2018). (1) Due to the long-term of "duck-feeding" education in school, our students become heavily dependent on traditional Lecture-Based Learning (LBL), lacking the initiative and ability to discover and solve problems. Students get used to merely asking and answering questions, but lack the ability to solve problems. Some students have poor learning consciousness or even resist to discussion. (2) Clinical tutors always have dual identities. Their clinical work is very onerous and they have to undertake teaching. Sometimes their roles in teaching are not clear. It is even believed that the difference between PBL and LBL is only the exchange of roles between students and teachers, that means, students are the speakers of the class, while teachers are the listeners and evaluators. (3) To train the students to independently bring out issues, analyze and solve problems, tutors are more inclined to simply listen to discussion and evaluate their performance, allowing students to play their part ad lib. This may lead to a deviation from the direction of learning and ultimately a serious loss of learning objectives. In fact, students hope that the tutor can play a more guiding role to in curriculum implementation (AlHaqwi, 2014; Chang, 2016).


In this study, to solve the above mentioned issues, we design and develop a novel learning method, Navigation-Based Learning (NBL), for medical students in clinical thinking training. In NBL curriculum, the tutors actively guide students to participate in the whole learning process, create and maintain the atmosphere of discussion, simulate the clinical diagnosis and treatment scenarios, help students to establish clinical logical reasoning and strengthen clinical thinking, finally complete the learning objectives efficiently.


1. Case design and hardware construction

We design and establish a NBL case library through compiling the authentic clinical records. Each case comprises two acts. The content of Act Ⅰ include the chief complaint, history of present illness, past medical history and abnormal physiological indicators and signs. The content of Act Ⅱ include the actual clinical diagnosis, therapeutic schedule and prognosis. According to the standard PBL curriculum, we also revise several cases for PBL control group. All cases are approved by ethical review and rationality verification. We also establish an exclusive classroom for NBL, which is equipped with computer, projector, blackboard, wireless network, electronic literature database, etc. The classroom is separated into two compartments, students and tutor room and observers room. The single-blind observers can synchronously evaluate the performance of students and tutor (Figure 1).


Figure 1. A standard NBL classroom. (A) students and tutor room, (B) observers room.


2. Methodological framework

A standard learning group includes one tutor and ten students. The tutor’s role includes organization of the learning process and control of the pace. The NBL case is randomly selected from the library and the whole study of single case is tightly completed in three hours. The learning process of NBL is designed as follows. (1) Step 1: Introduction (10 min). The tutor generally explains the learning procedure and the students introduce themselves. Throughout the learning process, students should take notes by themselves and prepare their own multimedia equipment for real-time web access. (2) Step 2: Act Ⅰ (75 min). The students read materials of Act 1, take preliminary analysis and judgment of physiological abnormalities, and brainstorm a list of issues. Subsequently, the students freely form teams according to the issues they are interested in. Each team enters the stage of deep-learning by self-organize. Students get the initial diagnosis of the disease and enumerate the basis of diagnosis by quickly inquiring the web resource and so on. Finally, the tutor guides the students to participate in a collective discussion and summarize a consensus, then confirms the rationality of the pre-diagnosis. (3) Step 3: Act Ⅱ (75 min). The students read materials of Act Ⅱ. The tutor helps the students to self-examine, answers the questions, improves the pre-diagnosis and summarizes the learning results of Act Ⅰ. Then tutor guides the students to study the treatment and prevention parts. After collaborative learning in teams, the students take in a collective discussion, supplement and answer the remnant questions. (4) Step 4: Summary (20 min). Finally, the tutor summarizes the case. The students further review their notes after class and complete their reports.


3. Population

A total of 300 students majoring in clinical medicine are recruited to participate in NBL course (Table 1). These students all have complete experience of three PBL cases, including 165 males and 135 females. For educational system, these students include 249 of eight-year clinical medicine (8Ymed) in combined bachelor's and master's degree, 51 of five-year clinical medicine (5Ymed) in bachelor's degree. For control study, another 300 students participate in standard PBL course, using the relevant revised cases. All students are informed the purpose of the course and volunteer for the research study.


Table 1. Baseline characteristics of students in NBL curriculum


Constituent Ratio



Male (55%)     Female (45%)


Educational system

8Ymed (83%)     5Ymed (17%)



Grade 1 (12%)     Grade 2 (65%)     Grade 3 (23%)



General clinical medicine (56%)     Stomatology (20%)    Pediatrics (18%)     Ophthalmology (3%)     Psychiatry (3%)


4. Quality evaluation and data quantization

The learning quality of NBL or PBL is evaluated when course finished. It consists of two parts: the objective in-class test of professional knowledges, and the subjective questionnaire about the comparison between NBL and PBL. All students complete the tests and questionnaires anonymously.


According to the medical knowledges involved, ten questions with varied difficulty levels are designed for each case. Each question has 10 scores and 100 scores in total. These questions could also be typed into four different fields. (1) Symptoms and Signs. Symptoms mainly refer to the personal statement, such as headache, abdominal pain and so on. Signs refer to the abnormal changes found by the doctor when examining the patient. (2) Diagnosis, it mainly includes the basis of diagnosis of diseases and differential diagnosis of other diseases. (3) Treatment and Prevention, it mainly includes drug treatment, surgical treatment, post-operative nursing, preventive measures and so on. (4) Etiology and Pathogenesis, it mainly refers to the pathological changes within the body and the factors of increasing the disease occurrence probability.


The questionnaire based on comparison between NBL and PBL is designed, which include the following factors: (1) general approval rating, (2) learning efficiency of unit time, (3) clarified learning orientation, (4) collaborative skills, (5) clinical simulation, (6) clinical thinking, (7) tutor’s navigation role and so on. The score of each question ranges from 0 to 100, increasing every 10 scores. The score greater than or equal to 60 is defined as a positive attitude, while less than 60 is defined as a negative attitude. The NBL confidence index is defined as positive attitude of 1 and negative attitude of 0, according to the scores of general approval rating.


5. Statistical analysis

All data are analyzed using SAS 9.1 software. Chi-square test is used for counting data, and mean ± standard deviation (or standard error) is used for measuring data. T test and F test are used for comparison between groups, p < 0.05 is significant difference.


1. Objective evaluation of NBL learning quality: Examination

The average score of NBL group is 69.67 ± 12.54 (mean ± S.D.), slightly lower than 73.20 ± 13.14 in PBL group. The results of statistical analysis are p=0.388 in F-Test (two-sample for variances) and p=0.311 in t-Test (two-sample assuming equal variances), showing no significant difference between two learning methods. Firstly, we analyze the scoring of NBL and PBL in different fields (Figure 2a). The average score of NBL is slightly higher than that of PBL in symptoms and signs, diagnosis parts, and slightly lower than PBL in treatment and prevention parts. But the statistical results show no significant difference between NBL and PBL. However, in etiology and pathogenesis parts, the average score of NBL (66.67 ± 4.71) is lower (p=0.020) than that of PBL (71.30 ± 3.46). This may be due to the fact that NBL has compressed the whole course time than PBL, the study of etiology and pathogenesis is not as deep and solid as that of PBL, especially knowledges related to the field of basic medicine. These knowledges could be further supplemented by an after-class review.


Figure 2. Quantitative analyses of detailed scoring in NBL and PBL.


Table 2. Statistical analysis of scoring based on the difficulties of questions

Degree of Difficulty

NBL Scoring

PBL Scoring


p value


p value


Standard Deviation


Standard Deviation








































































Secondly, we analyze the scoring of NBL and PBL according to the difficulty levels. The results show no significant difference (Table 2). We conduct the linear regression analysis (Kotter and Niebuhr, 2016; Liang et al., 2018). The regression equations are YNBL= -0.088X + 1.178 ( = 0.892) and YPBL= -0.083X + 1.177 ( = 0.918). Here, X represents the difficulty and Y represents the accuracy (Figure 2b). To determine whether two slopes of NBL and PBL equal, we apply statistical analysis and the results are F=0.562 and p=0.457, which indicate that if the overall slopes are identical, there is a 46% chance of randomly choosing data points with slopes this different. So we can conclude that the differences between the slopes of NBL and PBL are not significant. Next, to determine whether the elevations or intercepts equal, we apply statistical analysis and the results are F=1.944 and p=0.169, which indicate that if the overall elevations are identical, there is a 17% chance of randomly choosing data points with elevations this different. Taken together, we can conclude that the difference between the correctness curves of NBL and PBL are not significant. Furthermore, since the slopes and intercepts are not significantly different, it is possible to calculate single slope for all the data. The pooled slope equals -0.085. It is also possible to calculate single Y intercept for both NBL and PBL. The pooled intercept equals 1.177. Therefore, in the practices of NBL or PBL, the functional relationship between accuracy and the difficulty levels can be expressed as a single regression equation: YNBL/PBL= -0.085X + 1.177.


Thirdly, we analyze the scoring proportions of NBL and PBL through various statistical models (Bland and Altman, 2004; Omata et al., 2018). The results are χ2=1.364, p=0.243 in Mantel-Cox test and χ2=1.203, p=0.273 in Gehan-Breslow-Wilcoxon test, which indicate no significant difference between the two scoring curves (Figure 2c). However, compared with PBL, the hazard ratio (HR) of NBL is 1.085 (0.872-2.327, 95% C.I.) in Log-rank analysis, indicating that the risk (equals to error probability) of NBL is 1.085 times that of PBL. On the contrary, compared with NBL, the HR of PBL is 0.967 (0.361-1.125, 95% C.I.), indicating that the error probability of PBL is 0.967 times that of NBL. These results demonstrate that along with the increasing difficulties, the risk of loss scoring in NBL is approximately 8.5% higher than that in PBL. But in general, the above analyses show that NBL can achieve similar learning quality as PBL. Considering that NBL strengthens tutor guidance and greatly reduces the overall time than PBL, it can conclude that NBL has a higher learning efficiency.


2. Subjective evaluation of NBL learning quality: Questionnaire

Generally, the approval rating of NBL curriculum is 85.11%, with an average score of 81.50 ± 14.42 (mean ± S.D.) and the mode score of 100 (25.53%). For learning efficiency of unit time, NBL reaches an 80.85% approval rating with an average score of 80.53 ± 13.55 and the mode score of 80 (27.27%). For clarified learning orientation, NBL reaches an 82.97% approval rating with an average score of 79.49 ± 13.37 and the mode score of 80 (21.28%). The NBL course is more compact in time than PBL. Students focus around solving clinical problems under the guidance of tutor, so greatly improve the learning efficiency. For collaborative skills, NBL reaches an 80.85% approval rating with an average score of 80.00 ± 14.14 and the mode score of 70 (21.28%). Since each team focuses on its objectives and excavates enough in-depth information, they can collaboratively construct a complete interpretation of the case. For simulation of clinical diagnosis and treatment scenarios, NBL reaches an 85.11% approval rating with an average score of 81.75 ± 14.48 and the mode score of 80 (29.79%). For clinical thinking and logical reasoning, NBL reaches an 85.11% approval rating with an average score of 83.50 ± 14.06 and the mode score of 100 (27.66%). NBL uses limited time to simplify the course content and learning process, so naturally improves the acceptance of the course. The clinical consultation and situation in NBL course are simulated more truthfully than PBL, so as to cultivate the clinical thinking and logical reasoning. For tutor’s navigation role, NBL reaches an 76.60% approval rating with an average score of 81.94 ± 14.51 and the mode score of 80 (25.53%). Because the expertise and teaching behavior of tutors have a great impact on students' learning effect (Dolmans and Wolfhagen, 2005; Chng, Yew and Schmidt, 2011; Lee, Lin and Lin, 2013). NBL emphasizes the guidance of tutor, so that students can target the diagnostic clues and find the optimal therapeutic regimen more efficiently.


The popularity of a new learning method is influenced by many factors. Simply comparing a single score hardly reflect deeper information, such as the key factors involved in the questionnaire and their different weights. In order to reveal which factors mentioned above are essential to influence the popularity of NBL, we apply the epidemiological analysis model and the univariate logistic regression analysis (Armstrong et al., 2012; Direkvand-Moghadam et al., 2016). The statistical relationship between these factors and NBL confidence index are quantitatively analyzed. The results show that four factors have significant statistical correlation with NBL confidence index (Table 3). For learning efficiency of unit time (p=0.029), the HR of students with positive attitude is 1.119 (1.011-1.239, 95% C.I.), indicating that the probability of positive attitude is 11.9% higher than that of negative attitude. For Clarified learning orientation (p=0.039), the HR of students with positive attitude is 1.093 (1.005-1.189, 95% C.I.), indicating that the probability of positive attitude is 9.3% higher than that of negative attitude. For simulation of clinical diagnosis and treatment scenarios (p=0.033), the HR of students with positive attitude is 1.139 (1.011-1.284, 95% C.I.), indicating that the probability of positive attitude is 13.9% higher than that of negative attitude. For clinical thinking and logical reasoning (p=0.033), the HR of students with positive attitude is 1.089 (1.007-1.178, 95% C.I.), indicating that the probability of positive attitude is 8.9% higher than that of negative attitude. However, there are two factors, tutor’s navigation role (p=0.117) and collaborative skills (p=0.088), showing no significant statistical correlation with the approval of NBL. This demonstrates that although the guidance role of tutor is obviously enhanced in NBL, it does not affect the support attitude towards NBL.


Table 3. Univariate logistic regression analysis of risk factors in NBL confidence index

Risk Factors


Standard Error





Hazard Ratio

95% C.I. HR



Learning efficiency









Clarified orientation









Clinical simulation









Clinical thinking









Collaborative skills









Navigation role









We also analyze the suggestions on NBL curriculum in the questionnaire. In terms of NBL course time, 59.57% of students agrees with the current time, believing that the three-hour course could maintain a better balance between learning efficiency and content. Only 12.77% of students demands an additional half-one hour to complete the in-depth study. Many students hope to add some performance evaluation in the autonomous learning stage, which requires further improvement of the process evaluation system, such as joining an independent third-party observer. In addition, students suggest the tutors to bring their own experience into class, not only organize the course. Students need more learning guidance from first-line clinicians, rather than the rigid pattern of finding keywords and raising issues under the student-chaired course in PBL. In addition, some students also suggest to classify the case library on the basis of clinical departments, organs, diseases and so on, so that students can choose the case they are interested in more conveniently.


According to previous report, 70% of the students are more inclined to clinical-oriented case study after completing the basic course of PBL (Aljarallah and Hassan, 2015). But PBL or Case-Based Learning (CBL) are too standardized and procedural in issues description, and students are prone to lose interest after several studies (Sun, Chen and Wu, 2018). To stimulate the learning interest and enhance the motivation for autonomous learning, it should create an authentic clinical situation. In this study, the design of ill-structured NBL curriculum has very high requirements for clinical scenario simulation. It is devoted to creating an atmosphere of clinical multidisciplinary consultation and simulating an authentic clinical situation.


The new learning strategy NBL has three characteristics. (1) NBL requires students to have basic medical knowledges and is not suitable for all students. The first act of NBL course is mainly about clinical signs, physiological and pathological indicators, the junior students lacking systematical studies of clinical courses will be difficult to combine physical signs with clinical indications. So students, especially those entering medicine directly from school, are unable to form a preliminary understanding of the disease and finally result in low efficient learning. (2) NBL strengthens the active guidance and control of tutor over the course. It requires tutor to guide students according to clinical scenario, so as to avoid excessive divergent and aimless learning that often occurs in self-driven spontaneous discussion. Generally, NBL greatly reduces the course time, enhances the direction of learning and improves the learning efficiency. (3) NBL curriculum is designed from the actual cases. It helps students to understand the actual clinical diagnosis and master the therapeutic regimen following certain diagnostic guidelines, and building a good foundation for future clinical work.


In this study, the NBL learning strategy is firstly proposed. Our results indicate that NBL is an effective learning method in clinical thinking training for medical students. NBL is featured by enhancing tutor’s guidance and simulating the clinical scenarios. It achieves a balance between promoting efficiency and maintaining interest in medical learning.

Take Home Messages

  1. NBL achieves comparable learning quality as PBL and reaches a higher efficiency than PBL.
  2. NBL emphasizes the guidance role of tutor and greatly compresses the overall course time.
  3. NBL strengthens the authentic simulation of clinical diagnosis and treatment scenarios.

Notes On Contributors

Yi-Zhou Wu is an assistant professor of cell biology at School of Basic Medicine Nanjing Medical University, P.R.China. Dr. Wu’s research mainly focuses on developing novel methodology in higher medical education, including artificial intelligence and deep-learning algorithms.



Jie Sun is an assistant professor of pharmacy at School of Public Health Nanjing Medical University, P.R.China. Dr. Sun’s research mainly focuses on the application of problem-based learning and e-learning, designing the medical curriculum.



The authors would like to thank all students and teachers who volunteered to participate in this research.


Yi-Zhou Wu is the creator/owner of Figure 1.

Jie Sun is the creator/owner of Figure 2.


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There are no conflicts of interest.
This has been published under Creative Commons "CC BY-SA 4.0" (

Ethics Statement

This study was approved by institutional review board of Nanjing Medical University (No.12063).

External Funding

This study was supported by Natural Science Foundation of Jiangsu Province (BK20171050, BK20180676), Natural Science Foundation of the Jiangsu Higher Education Institutions of China (17KJB310006), Innovative Training Program of Jiangsu Undergraduates (201810312053X, 201810312063X).


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Ken Masters - (09/12/2019) Panel Member Icon
An interesting paper dealing with the design and practice of navigation-based learning (NBL) as a novel method for clinical thinking training.

While the method of teaching certainly sounds to be worthwhile, and certainly has the approval of the students, I do have two issues:

1. The problems with PBL, as outlined in the paper, appear to be not so much a problem with PBL, but more on how the PBL had been implemented.
a. This is evidenced strongly by the fact that the cases had to be re-designed for the PBL control groups, which would indicate that the original PBL cases had flaws (or were boring, not drawn from realistic data, etc.). “NBL curriculum is designed from the actual cases” – perhaps the PBL cases could also be constructed in the same way. Yes, they were re-constructed for this running of the course, but it is possible that the damage had already been done, and PBL had a poor reputation, so any new method would be good.
b. From the descriptions of the PBL process given in the paper, it would appear that the PBL facilitators were either not well trained, or, perhaps, had become somewhat jaded (as can happen, especially when cases are repeated year after year). A good case cannot rescue poor facilitation.

2. Long term: The long-term evaluation of the NBL system really is required.
a. As noted above, staff become a little jaded with repeated cases, so this may happen to NBL also.
b. Students share information with the next years’ students, so, after a year or two, it would be interesting to see whether or not the students are similarly giving lip-service to the process (and getting the information from the previous years’ students) or actually performing the required deep learning tasks. Many excellent constructivist teaching approaches (including PBL and TBL) are undermined by students’ sharing information from year to year, and the only real solution is the design of new cases and questions and tasks every year – something that is not easily sustainable.

I would like to see the authors address these two issues explicitly in their Discussion.

The paper has quite a large number of minor language errors, and I would like to see Version 2 of this paper more closely proof-read, please.

So, I do think that what the authors have designed is of value. I also think, however, that its value as shown in these results might be somewhat inflated because (1) it is being compared to a process that may be badly implemented, and (2) three years would be the minimum number of years required to really report on the effectiveness of this.

Possible Conflict of Interest:

For transparency, I am an Associate Editor of MedEdPublish. However I have posted this review as a member of the review panel with relevant expertise and so this review represents a personal, not institutional, opinion.

Trevor Gibbs - (09/09/2019) Panel Member Icon
As someone who teaches extensively in mainland China I was very interested to review this paper and understand what the authors proposed in this relatively new approach to learning, Navigation-Based Learning ( NBL)

I enjoyed reading the paper but like my co-reviewer I think that the authors have "missed the point" somewhere in the design of NBL.

I would agree with the authors that PBL does not always sit easily within the Chinese context where learning is frequently based on the accumulation of facts and applying these as best as possible to cases, sometimes without a large amount of clinical reasoning happening. Many schools are now trying hard to change this model by the introduction of PBL which encourages a more deeper form of learning through its utilisation of educational theory. Again as the authors rightly point out, the real PBL model is frequently modified to suit the clinical climate and short cuts are taken, so that much of the PBL is in fact Case-Based Learning. I feel that the authors did not in this paper expand enough on how PBL was previously used, which might seriously influence their perceptions of PBL.
Students are students the whole world over and "like" the approach of being told what they need to know, (encouraging superficial learning) , rather than engaging in directed self learning ( as PBL offers and stimulates deeper learning) . Hence I am not convinced at present that the authors can be as dogmatic in their conclusions as they are.
PBL also allows exploration of all learning domains, especially the Affective Domain, which is so important in any form of clinical learning - I could not see it being discussed in the NBL model.

One other advantage of PBL or other forms of learning based on sound educational theory is their longer term effects ( the result of deeper learning). I would be interesting to look at a longer-term evaluation of NBL , looking specifically at the retention and application of their new learning.

Although I have been critical of this NBL model, I would encourage them to continue their work in curriculum development, and whilst I am not in complete agreement with their paper's content and conclusions I would suggest that it would make an interesting read for all those involved in curriculum planning.
Possible Conflict of Interest:

For transparency, I am one of the Associate Editors of MedEdPublish

Raul Sampieri Cabrera - (09/09/2019)
The authors present an interesting work, however I believe that the discussion of results should be strengthened.
When talking about deep learning, the authors must emphasize what is necessary to have a superficial learning first.
I think your strategy can contribute to the transfer of learning.

Let me quote textually a work in this regard, which would be very interesting for them to use in their discussion of results.

"Why some strategies do not work?
The fifth set of claims relate to how the model can be used to resolve some of the unexpected findings about the impact of various teaching methods. In Visible Learning, 36 it was noted that many programs that seem to lead to developing deeper processing have very low effect sizes (e.g., inquiry based methods, d=0.31; problem-based learning, d=0.15). For example, there have been 11 meta-analyses relating to problem-based learning based on 509 studies, leading to an average small effect (d=0.15). It hardly seems necessary to run another problem-based program (particularly in first-year medicine, where four of the meta-analyses were completed) to know that the effects of problem-based learning on outcomes are small. The reason for this low effect seems to be related to using problem-based methods before attaining sufficient surface knowledge. When problem-based learning is used in later medical years, the effects seem to increase. Albanese and Mitchell 86 claimed that increased years of exposure to medical education increases the effect of problem-based learning. They argued that lack of experience (and lack of essential surface knowledge) leads the student to make more errors in their knowledge base, add irrelevant material to their explanations and engage in backward reasoning (from the unknown to the givens), whereas experts engaged in forward reasoning (also see references 87,88). Walker et al. 89 also noted that novice problem-based learning students tended to engage in far more backward-driven reasoning, which results in more errors during problem solving and may persist even after the educational intervention is complete. It is likely that problem-based learning works more successfully when students engage in forward reasoning and this depends on having sufficient content knowledge to make connections.

Deep understanding in problem-based learning requires a differentiated knowledge structure, 90 and this may need to be explicitly taught—as there is no assumption that students will see similarities and differences in contexts by themselves. There is a limit to what we can reasonably expect students to discover, and it may require teaching students to make predictions based on features that were told to them and that they may not notice on their own. Deliberate teaching of these surface features can offer a higher level of explanation that would be difficult or time consuming to discover. A higher level explanation is important because it provides a generative framework that can extend one understanding beyond the specific cases that have been analysed and experienced. On the other hand, the problems need not be too overly structured, as then students do not gain experience of searching out conceptual tools or homing in on particular cases of application"

Learning strategies: a synthesis and conceptual model
John A C Hattie & Gregory M Donoghue
npj Science of Learning volume1, Article number: 16013 (2016)

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