Evaluation of an Interactive and Collaborative Cloud-based Learning Strategy in Medical Education

doi:10.21203/rs.3.rs-4864145/v1

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Research Article

Evaluation of an Interactive and Collaborative Cloud-based Learning Strategy in Medical Education

https://doi.org/10.21203/rs.3.rs-4864145/v1

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Background

In most health professions education programs, didactic lectures remain the most common teaching modality. There is a need for synchronous interactive instructional methods that require little student preparation, promote directed-independent learning and high-order cognition, while increasing feedback and teamwork. We have recently created a Cloud-based learning (CL) educational tool that uses the conceptual Technological Pedagogical Content Knowledge (TPACK) theoretical framework, together with generative learning theory. Using student surveys, we aim to evaluate this instructional methodology and compare it with more common practices in medical education, including Team-Based Learning (TBL), Flipped Class (FC), and Didactic Lectures (DL). In addition, using a literature-based analysis, we compared CL to several instruction methods (DL, PBL, TBL, FC) to determine whether CL has unique characteristics that differentiate it from other instructional methods.

Methods

Student perception surveys were used to contrast responses regarding these instruction methods in terms of satisfaction, student preparation time, teamwork, collaboration, and formative feedback received. Responses were analyzed using the Kruskal-Wallis H-test and Dunn’s pairwise test to determine statistical significance between the medians.

Results

Compared to other teaching methods, students expressed a preference for TBL and DL over CL and FC (DL = TBL = CL > FC). CL and DL were perceived to require the least preparation time (less than 30 min), compared to FC and TBL (CL = DL < FC < TBL). Regarding the learning environment and engagement with each of the instructional strategies, participants were equally engaged with TBL, DL and CL, and less engaged with FC (TBL = CL = DL; TBL > FC). TBL and CL were rated significantly higher in terms of collaboration and teamwork, in which CL provided significantly higher instructor feedback than TBL, DL and FC (CL > TBL > DL = FC), while TBL provided significantly higher peer feedback than CL (TBL > CL > DL > FC).

Conclusions

Despite the benefits of CL (student preparedness, high feedback and collaborative environment), students express preferences toward TBL and DL. Compared with existing teaching methods, CL has some unique characteristics that enable students to create their own study tool with reduced preparation time, strong feedback and a collaborative environment that can be considered an alternative educational strategy.

Cloud-based technology

Didactic lecture

Flipped Class

Generative learning

Google document

Problem-based learning

Team-based Learning

Technological Pedagogical Content Knowledge

The internet has radically changed medical education. In 1998, the World Federation for Medical Education (WFME) made recommendations concerning the use of computers in medical school classrooms, among which they recommended: 1) access to computers, the internet, email, for students and faculty, 2) using the internet to exchange educational materials, and 3) rewarding teachers for computer-related education work (1). Medical students have demonstrated a preference for learning using the internet over textbooks (2) and internet-based continuing medical education programs have been shown to be just as effective as traditional formats at teaching doctors new medical information (3). The WFME have more recently updated their quality standards (section 6.3) indicating that medical schools should enable teachers and students to use existing and exploit appropriate new information and communication technology for independent learning, accessing information, managing patients and working in health care delivery systems with others in order to prepare students to be evidence-based practitioners and to promote life-long learning (4).

Modern college and medical courses rely on technology in the learning environment for many purposes; online course organization learning management systems (Moodle™, Blackboard™, etc.), and self-learning tools (modules, quizzes, videos, recorded lectures) now dominate post-secondary education (5). In 2013, five universities in Europe undertook the innovative ‘Media Project 2020’ initiative, with the goal of developing technology use in the classroom. ‘Media Project 2020’ created workshops where students and faculty could discuss new and different ways of facilitating teaching through social media, mobile devices, cloud-based technologies and other online platforms. They used Google Drive™ to share information, ideas, and research sources, and collaborate on shared word-processing documents. The initial report found ‘Media Project 2020’ to be a success, with technology enhancing the experience of students and lecturers by increasing collaboration and communication (6).

Many medical students now choose to learn by watching recorded lectures rather than attending live lectures (7). This change is due, in part, to recent improvements in cloud-based technology as online systems can allow multiple users with personal computers in different locations to edit and view the same file simultaneously, fostering collaboration and team learning (8). Cloud-based document editing has been used successfully by college undergraduate students for group lab reports in a physics lab and the professor even tracked the contributions of each group member by using the ‘revision history’ feature (9). Cloud-based technology has also been used in several instructional methods and interactive sessions [i.e, team-based learning (TBL) and Think-Pair-Share] that promote a highly collaborative environment allowing students to think beyond the content of the required readings (10, 11). Instructions in which cloud-based technology are used to take notes in teams, improve student classroom performance (grades) and allow instructor feedback (12, 13). Thus, taking advantage of cloud technology in instruction methods is essential to effectively improve the learning environment.

Medical school requires high-order cognition (14). Didactic lectures (DL) have been shown to be one of the least effective methods for students to learn, resulting in researchers promoting more interactive and relevant educational tactics (15–18). To assist students with different learning preferences, many medical schools now include learner-centered approaches in the classroom (19, 20). This push has spurred the creation of teaching modalities that are more interactive and meaningful to students. Several commonly used teaching styles, including TBL, problem-based learning (PBL), and flipped classroom (FC), have attempted to meet the needs of the students by engaging learners, promoting team learning, providing immediate feedback to students and facilitating higher-order cognitive skills (21, 22). However, students have reported these classroom styles require an increased preparatory work in order to be sufficiently effective (21, 23).

Integrating technology, pedagogy and content knowledge into teaching is important for an effective learning environment, as described in the theoretical framework Technological Pedagogical Content Knowledge (TPACK) (24). This conceptual theoretical framework, together with generative learning theory provide a unique and strong environment for learning and teaching as generative learning theory enables learners to develop an understanding of the material that they can apply in new situations (25). Generative learning strategies such as summarizing, mapping, reflection, and self-explaining (26) target the highest cognitive domain of Bloom's taxonomy (27) as participants create their own study material (28). Thus, creating an instructional educational design that applies constructivist pedagogy (29, 30) in which instructors use the TPACK framework (24) and enable students to create their own study tool with reduced preparation time would be a powerful instructional design educational activity.

We recently developed an interactive instructional session that integrates disciplines, contains real-time instructor feedback, and promotes teamwork in a large class setting using online collaboration technology (i.e., google doc) (31). The session allows participants to learn new content and create their own study guide. Pre- and post-assessments of this Cloud-based Learning (CL) session showed the student knowledge increased 2.5-fold, and students were satisfied with this instructional method (31). The major aim of the current study is to evaluate student perceptions of CL instruction, and compare it (in terms of student preparation time, feedback, and collaboration) to other accepted instructional methods, including TBL, flipped classroom (FC) and DL. In addition, we investigated the major aspects that differentiate CL from various other instructional methods that are commonly used in health professions education.

The aim of this study was to evaluate student perceptions of CL instruction, and compare it to other accepted instructional methods (TBL, FC and DL). The major aspects that differentiate CL from other commonly used health professions education instructional methods were also investigated. The setting of this study was in the preclinical medical education curriculum of a single medical school in the United States.

Participants

The study participants were first-year undergraduate medical students at Oakland University William Beaumont School of Medicine enrolled in the winter semester Respiratory organ systems course during 2016–2019. Medical students were divided into teams of four to six per team and were familiar with working in these small groups from previous experience with TBL. The study was approved by the Oakland University IRB, study number 840485.

CL session

As described previously (31), CL consists of formative assessments and collaborative learning. Prior to participation in CL, students received an email from study personnel providing brief information about the upcoming instruction, including a Google Drive™ spreadsheet access link. Briefly, the CL session was organized as two sequential 50-minute integrated sessions of microbiology and immunology as a part of the respiratory organ system curriculum. Two faculty members were responsible for the delivery of material and coordination of the session, covering topics of mucosal immunity and Mycobacterium tuberculosis infections. Medical students work in teams to complete an online collaborative spreadsheet that instantly updates for all participants, while instructor(s) provide real-time formative feedback. The template files, PowerPoint session, google spreadsheet with questions, and formative assessments have been previously described (31).

Questionnaire

An IRB-approved questionnaire (see Additional File 1 for the list of questions) was administered to students who provided consent in order to evaluate satisfaction, collect suggestions for improvements, and better understand how CL might facilitate student learning. In general, questions on learning modalities were grouped such that questions referring to TBL were first, followed by CL, DL, and finally FC.

Data analysis

Data were collected using Likert scales (ordinal data) where the categories have a meaningful order, but the intervals between them may not be equal. Consequently, median values were utilized in the research analyses instead of mean values, acknowledging the ordinal nature of the Likert scale. Specifically, the Kruskal-Wallis test was employed to assess whether there are statistically significant differences in the medians of student experiences across these instructional methods. Dunn’s pairwise test was used to determine statistical significance between group medians.

We designed an instructional teaching session for a large classroom setting (Fig. 1)(31), which incorporates formative assessment, uses collaborative technology to engage students, promotes teamwork, and allows students to create their own content. Previously in the curriculum, our students had been exposed to the teaching strategies of DL, TBL, and FC and our survey asked them to compare various aspects of their experiences with those teaching strategies to this new CL strategy. Statistically significant differences were found when we analyzed the portions of the questionnaire pertaining to student satisfaction, preparation time, student collaboration (engagement and teamwork), and perceptions of formative feedback. The questionnaire was administered to all students over 4 years of instruction and the total number of students completing the survey was 114. The median age of participants was 23.8 years (SD = 1.6 years). Thirty-seven percent of participants were male, and 63% were female (31).

Student satisfaction

Students were asked to rate their level of satisfaction/dissatisfaction with each of the four instructional strategies on a 6-point Likert scale (Questions 1–4 of the questionnaire; 1 = strongly dissatisfied, 6 = strongly satisfied). The percentage of students (N = 111) who responded slightly satisfied to strongly satisfied (4–6 on the 6-point Likert scale) was 87% for TBL, 84% for DL, 74% for CL, and 46% FC. When comparing the median satisfaction using a Kruskal-Wallis test we found that DL, TBL and CL had the highest student satisfaction, which was higher than FC (DL = TBL = CL > FC; H = 44.411, p < .001; Table 1). Separately, but on the same questionnaire (Q74), participants were asked to rank the instructional methods in terms of their own satisfaction (N = 106), and we found that DL was ranked significantly higher than FC, CL, and TBL, and that TBL was significantly different compared to FC (DL > TBL = CL = FC; TBL > FC; H = 37.113 (3), p < .001).

Preparation time

Student perception of preparation time was measured on a 5-point scale (N = 54; Questions 21, 38, 55, 72; 1 = < 30 min and 5 = > 120 min). As expected, preparation time was perceived to be the lowest and similar for DL and CL (less than 30 min), when compared to FC (> 90 min) and TBL (> 120 min) (CL = DL < FC < TBL; H = 122.366 (3), p < .001; Table 1).

Engagement and teamwork/collaboration

When comparing student responses to three individual questions regarding learning environment and engagement with each of the four instructional strategies on a 5-point Likert scale (N = 55; Q5-7, Q22-24, Q39-41, Q56-58; 1 = not at all, 5 = a lot). We found that participants were equally engaged with TBL, DL and CL, and less engaged with FC (TBL = CL = DL; TBL > FC, H = 12.153 (3), p = .007, Table 1). TBL and CL were rated significantly higher in terms of collaboration and teamwork on a 5-point Likert scale (N = 54; Q16-18, Q33-35, Q50-52, Q67-69, 1 = not at all, 5 = a lot) than DL and FC and TBL is significantly higher than CL (TBL > CL > DL = FC, H = 68.789 (3), p < .001, Table 1).

Table 1

Student perceptions of instructional strategies.
Feedback	CL Mean; Median (SD, N)	TBL Mean; Median (SD, N)	DL Mean; Median (SD, N)	FC Mean; Median (SD, N)	CL vs TBL	CL vs DL	CL vs FC	TBL vs DL	TBL vs FC	DL vs FC
Student satisfaction	4.12; 4.00 (1.21, 111)	4.49; 5.00 (1.02, 111)	4.46; 5.00 (1.18,109)	3.36; 3.00 (1.55, 111)	n.s.	n.s.	< 0.01	n.s.	< 0.01	< 0.01
Preparation Time	1.14; 1.00 (0.53, 51)	3.50; 3.00 (1.02, 54)	1.22; 1.00 (0.63, 54)	2.19; 2.00 (1.23, 54)	< 0.01	n.s.	< 0.01	< 0.01	< 0.01	< 0.01
Engagement	3.04; 3.33 (0.76, 55)	3.22; 3.33 (0.68, 55)	2.95; 3.00 (0.65, 53)	2.70; 2.67 (0.86, 54)	n.s.	n.s.	n.s.	n.s.	< 0.05	n.s.
Teamwork & Collaboration	2.90; 3.00 (1.07, 54)	3.56; 3.67 (0.84, 54)	1.92; 2.00 (0.79, 54)	2.23; 2.00 (0.98, 54)	< 0.05	< 0.01	< 0.05	< 0.01	< 0.05	n.s.

Table legend: The average responses for satisfaction (4 questions), preparation time (1 question), engagement (3 questions), and teamwork and collaboration (3 questions) were obtained from a survey using a 6-point Likert scale (satisfaction) or 5 Likert scale (other questions). A Kruskal-Wallis test was used to determine the median significant difference, and adjusted significance was calculated by Dunn’s pairwise tests for the six pairs of groups. Note that n.s. denotes no significance.

Formative feedback

We compared student responses to questions regarding overall feedback (individual questions regarding instructor and peer feedback combined) with each of the four instructional strategies on a 5-point Likert scale (N = 53; Q19-20, Q36-37, Q53-54, Q70-71; 1 = not at all, 5 = a lot). We found that the CL and TBL teaching methodologies were perceived to provide higher overall feedback when compared with FC and DL (CL = TBL > DL = FC, H = 66.115 (3), p < .001, Table 2). To determine whether overall feedback is from the instructor or their peers, we analyzed the results of the two questions separately. Participants perceived to receive significantly more feedback from the instructor in CL (N = 53; Q19, Q36, Q53, Q70), followed by TBL and DL and FC (CL > TBL > DL = FC, H = 67.710 (3), p < .001, Table 1). Feedback from peers (N = 53; Q20, Q37, Q54, Q71) was perceived to be significantly higher in both TBL and CL when compared with DL and FC (TBL = CL > DL = FC. H = 53.599 (3), p < .001, Table 2).

Separately, but on the same questionnaire, participants were asked to rank the instructional methods in terms of how much overall feedback was received (N = 102). In agreement with the separate questions above, TBL and CL were both perceived as providing significantly higher feedback when compared to DL and FC (Q73; TBL = CL > FC = DL H = 188.522 (3), p < .001).

Table 2

Student perceptions of feedback received in the instructional strategies.
Feedback	CL Mean; Median (SD, N)	TBL Mean; Median (SD, N)	DL Mean; Median (SD, N)	FC Mean; Median (SD, N)	CL vs. TBL	CL vs. DL	CL vs. FC	TBL vs. DL	TBL vs. FC	DL vs FC
Overall Instructor Peer	2.26; 2.00 (1.26, 53) 2.87; 3.00 (1.44, 53) 1.66; 2.00 (1.57, 53)	2.04; 2.00 (1.19, 54) 1.75; 2.00 (1.40, 53) 2.30; 2.00 (1.31, 54)	0.79; 0.00 (1.16, 53) 0.85; 0.0 (1.29, 53) 0.76; 0.0 (0.65, 51)	0.53; 0.00 (1.11, 53) 0.55; 0.0 (1.15, 53) 0.51; 0.0 (1.09, 53)	n.s. < 0.01 n.s.	< 0.01 < 0.01 < 0.05	< 0.01 < 0.01 < 0.01	< 0.01 < 0.05 < 0.01	< 0.01 < 0.01 < 0.01	n.s. n.s. n.s.

Table legend: Overall feedback is the average responses of 2 questions; feedback by instructors, and feedback by peers using a 5-point Likert scale survey. A Kruskal-Wallis test was used to determine the median significant difference, and adjusted significance was calculated by Dunn’s pairwise tests for the six pairs of groups. Note that n.s. denotes no significance.

Miscellaneous

Student perceptions regarding preparation for class exams (N = 110; Q8, Q25, Q42, Q59) and applications to clinical experiences (N = 54; Q9-11, Q26-28, Q43-45, Q60-62) showed a preference for TBL and DL over the other learning modalities (preparation for exams: TBL = DL > CL = FC; preparation for clinical experiences: TBL = DL > CL; TBL > FC; DL = FC; FC = CL). See Additional File 2 for statistical analysis of the data. Student perceptions about defining their own learning needs (N = 54; Q12, Q29, Q46, Q63) and monitoring their progress (N = 54; Q15, Q32, Q49, Q66) showed a preference for DL over the other learning modalities (define learning needs DL > CL = FC = TBL; monitor learning progress DL > TBL = CL = FC). Finally, student perceptions regarding information literacy/resources finding and validity (N = 54; Q13-14, Q30-31, Q47-48, Q64-65) showed a preference for CL over the other learning modalities (CL > FC = DL; CL = TBL; TBL = FC = DL).

Comparison of CL to other instructional methods

Our data support the notion that CL could be considered a unique instruction strategy. We compared CL with other instructional methods including TBL, FC and DL plus PBL (Table 3) (32–36). Although, we do not expect CL to replace other teaching methods, it simply can be a method that can be used in conjunction with others for a standard medical education curriculum. As shown in Table 3, CL compared to other instructional methods, does not require additional student preparation time, provides an interactive collaborative environment (group work) as well as instant feedback from professors and it is more student-centered. In addition, CL is unique as it provides pre and post assessments (31). A disadvantage is that CL requires more facilitators to deliver the session in order to provide instant feedback.

Table 3

Teaching method comparison.
	Student Preparation Time	Feedback		Student Collabora-tion	Assessment	Directed- Independent Learning	Other Benefits	Faculty/ facilitator Required
	Student Preparation Time	Peer	Instructor/facilitator	Student Collabora-tion	Assessment	Directed- Independent Learning	Other Benefits	Faculty/ facilitator Required
CL	None	Real time	Real time (per team and entire class)	Significant	Required: Formative	Significant	Student-centered; High-order cognition, Creation of study tool	Usually 2–4
TBL	Required	Real time	Real time (entire class)	Significant	Required: summative and/or formative	Significant: application portion	Student-centered; High-order cognition; learn how to apply pre-existing knowledge; uses peer assessment	Usually 1–3 (one for less than 48 students)
DL	None	Rare	Variable	Variable	Not required: Sometimes formative	Rare/variable	Familiar format for learners and faculty; exposure to new material	Usually 1
FC	Required	Rare	Variable	Variable	Not Required: Sometimes formative	Variable	Student-centered; High-order cognition	Usually 1
PBL	Variable	Real time	Guided by facilitator (per team)	Significant	Not Required: Sometimes formative	Significant	Student-centered; High-order cognition; learn how to learn new material	Many (one/ 8–16 students/group)

We developed an interactive session called CL that allows medical students to learn immunology and microbiology content and practice directed-independent learning using collaborative technology (Fig. 1) (31). We previously reported that student performance, measured as mean performance on pre-formative vs post-formative assessment, increased 2.55-fold while students indicated they were slightly satisfied to satisfied with the instructional session using CL instruction (31). Here our aim was to evaluate student perceptions of CL instruction, and to compare to other accepted instructional methods, including TBL, FC and DL.

When comparing questions of student perceptions regarding general satisfaction on a 6-point Likert scale or by ranking, we found that participants were equally satisfied with TBL, DL, and less satisfied with CL and FC (Table 1). In the preclinical years, the students at our institution spend ~ 53% of instruction as DL, 2.5% as TBL, and only 0.1% as FC (data not shown). Taken together, students appear to prefer the teaching style(s) that they are more familiar with (DL and to some extent TBL for our curriculum), similar to what has been previously reported at other institutions (37, 38). It is likely that other aspects of the CL session contributed to the reduced satisfaction by the students (i.e. timing of the session in the curriculum, team expectations, technical difficulties, organization problems, etc.) and that will be the focus of future research.

As expected, students perceived that TBL and FC required more preparation time when compared with CL and DL (Table 1). While TBL and FC require that students prepare before coming to class (21, 22, 27, 39), DL and CL do not require student advanced preparation. The curricular time assigned for CL remained the same as when this material was delivered as a DL instructional method. Students have reported that many classroom styles require prohibitory high advanced preparation in order to be sufficiently effective (21, 23, 36, 40), thus CL has an advantage when compared to TBL and FC, which does not require advanced student preparation.

Students perceived themselves to be equally engaged with TBL, DL and CL instruction, and less engaged with FC (Table 1). TBL is regarded as a highly learner-centered teaching method that, when conducted correctly, improves academic outcomes and learning measures as compared to other lecture-based teaching models such as DL and FC (21). In our curriculum, TBL requires in-person student attendance, and for students to arrive prepared, having studied provided advanced preparation material. With the exception of TBL, mandatory attendance is not common practice in our curriculum and advanced preparation is not required. Thus, student perceptions about engagement may have been compromised. In addition, our students are not exposed to FC commonly in the curriculum, so the rating of engagement as low for this instruction method is not surprising.

In terms of collaboration and teamwork, TBL and CL were rated significantly higher than DL and FC by the students (Table 1). In agreement with Ng, 2020 (39), the intrinsic nature of TBL with the use of teams and students working collaboratively, is similar to the instructional method CL and explains why these are perceived strongly by students. As expected, TBL provided more instructor and peer feedback than DL and FC. Surprisingly, CL was perceived by students to provide higher instructor feedback than TBL, while peer feedback received was perceived to be higher in TBL. Both TBL and CL teaching methods contain higher peer and instructor feedback when compared with DL and FC (Table 2, Table 3). The low mean obtained in the survey relating to feedback across all instructional methods was likely due in part to the high percentage of students who felt they did not receive feedback (DL (80%), FC (82%), TBL (40%) and CL (15%). The low mean for perceived peer feedback is similarly explained by some students reporting that they received no peer feedback. Instructor feedback in CL was provided instantly to all students as they were using the Google document (31), and also later when the material generated by students in class was compared to the material created by the instructor (Fig. 1), while TBL feedback is provided as a group. We speculate that the higher peer feedback rating of TBL is due to its familiarity during the interaction as a group, while in CL the feedback also requires writing the information in a document, which could reduce the personal interaction within the group.

When comparing assessment timing to other instructional methods, CL uses formative assessment before and after each session (Fig. 1, Table 3), while formative/summative assessment of TBL typically takes place at the beginning of iRAT. In general, no formative assessment takes place during FC or DL, as concepts are generally assessed afterwards on formal summative assessments, though this can vary. Higher perceived TBL engagement could therefore be explained as a consequence of the assessment timing; in most TBL sessions the RAT scores are graded and therefore students come prepared for sessions and have a more standardized initial level of knowledge, which may promote better discussion among peers, compared with FC and DL.

Our study has several limitations that should be recognized. The questionnaire that was administered to the students was not a validated survey. In addition, the sample size is small and student perception data were only collected from a single educational institution with one medical education curriculum. While our results cannot be generalizable, the description of this teaching method is publicly available (31) and may be used at educational institutions in order to generate more data on the effectiveness of this teaching strategy in the future.

CL integrates technology and uses the conceptual framework TPACK (24) as a content expert, technology, and pedagogy are integrated in this instructional method. CL also integrates the concepts of generative learning theory (25) as students create a study guide that summarizes and a matrix organizer to complete a given task (also aligns with the highest levels of Bloom’s taxonomy, namely creation, analysis, and synthesis (27)). These are generally not common in foundational courses in medical education (41). Our findings support the notion that CL has unique characteristics (Table 3) that provide formative feedback in order for students to monitor their own learning as required in medical education (Liaison Committee Medical Education Standard 9.7) (42). In our previous publication we found that students demonstrated short-term retention knowledge during CL (31), and future analysis to determine whether CL improves the learning outcomes of medical students, as well as its effectiveness on long term retention when compared with TBL, PBL and DLs is warranted.

CL uses the TPACK framework while encouraging generative learning in the classroom, and when compared to other teaching methods, CL has unique characteristics that could be considered another teaching method for large group setting, and a resource for synchronous teaching that is highly engaging and learner-centered.

Cloud Based learning

Didactic lecture

Flipped Classroom

LCME

Liaison Committee Medical Education

MCQ

multiple choice questions

PBL

Problem-based learning

TBL

Team-based Learning

TPACK

Technological Pedagogical Content Knowledge

WFME

World Federation for Medical Education.

Ethics approval and consent to participate: The study was approved by the Oakland University IRB, study number 840485.

Consent for publication: Not applicable

Availability of data and material: All data generated or analyzed during this study are included in this published article and its supplementary information files (additional file 1 and 2).

Competing interests: The authors declare that they have no competing interests.

Funding: No funding was obtained for this research project.

Authors' contributions: CC was involved in conceptualization, methodology, formal analysis and investigation, writing of the original draft as well as review and editing. TDJ was involved in formal analysis and investigation, writing of the original draft as well as review and editing. AMD was involved in methodology, as well as formal analysis and investigation. TAHT was involved in conceptualization, methodology, formal analysis and investigation, writing of the original draft as well as review and editing.

Acknowledgements: We thank Dwayne Baxa Ph.D., Mary Dereski Ph.D., Inaya Hajj-Hussein., Ph.D., Paul Megee, Ph.D. and Stefan Walter Ph.D. for providing student feedback during the teaching sessions. We also thank Daniel Gildner, Sean Taylor, and Boyun Kim for statistical analysis and support.

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No competing interests reported.

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Evaluation of an Interactive and Collaborative Cloud-based Learning Strategy in Medical Education

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Abstract

Background

Methods

Results

Conclusions

Figures

Background

Methods

Participants

CL session

Questionnaire

Data analysis

Results

Student satisfaction

Preparation time

Engagement and teamwork/collaboration

Formative feedback

Miscellaneous

Comparison of CL to other instructional methods

Discussion

Conclusions

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

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Version 1