International Journal of Interactive Mobile Technologies (iJIM) – eISSN: 1865-7923 – Vol  17 No  15 (2023) iJIM | Vol. 17 No. 15 (2023) International Journal of Interactive Mobile Technologies (iJIM) 171 iJIM | eISSN: 1865-7923 | Vol. 17 No. 15 (2023) | JIM International Journal of Interactive Mobile Technologies Milton, C., Subramaniam, A., Sridevi, S., Ganesh Kumar, S. (2023). Development and Testing of Mobile Assisted Language Learning Application to Improve Oral Clinical Case Presentation of Student Nurses. International Journal of Interactive Mobile Technologies (iJIM), 17(15), pp. 171–188. https://doi.org/10.3991/ ijim.v17i15.41675 Article submitted 2023-04-24. Resubmitted 2023-05-30. Final acceptance 2023-05-31. Final version published as submitted by the authors. © 2023 by the authors of this article. Published under CC-BY. Online-Journals.org PAPER Development and Testing of Mobile Assisted Language Learning Application to Improve Oral Clinical Case Presentation of Student Nurses ABSTRACT Background: Nurses’ oral case presentation is a core clinical communication skill with dis- tinctive linguistic qualities that require specific language training. The present paper is a user feedback analysis of a start-up Mobile Assisted Language Learning application (MALL app) developed and implemented to provide English language training to improve Oral Case Presentation (OCP) of student nurses pursuing baccalaureate degrees from a nursing college in South India. Objective: The aim was to develop and test an Android based OCP- MALL application for user acceptability and effectiveness in improving OCP performance and decreasing the perceived language difficulty. Methodology: Sixty-two  student nurses from a reputed nursing college in Chennai, South India, using Android mobile phones participated in the study. All the participants were given access and instructions on the use of OCP-MALL app. A comparison of pre and post-test of perceived level of language difficulty and OCP pre and post score along with users’ acceptance were collected. Results: The users’ acceptability showed that all participants rated the clarity in reading the text with highest mean score of 8.29 and std of 1.276, simplicity in navigation – moving to next page with next highest mean score of 8.19 and std of 1.526, clarity in text application layout with a mean score of 8.14 and std of 1.497 and user friendliness of the application with a mean score of 8.13 and std of 1.393. Conclusion: This startup OCP-MALL app user satis- faction feedback proves that Indian ELT trainers can create cost-effective and need-based m-learning applications. KEYWORDS mobile assisted language learning application (MALL), oral case presentation (OCP), student nurses, effectiveness, user satisfaction, English language training, m-learning Cynthia Milton1(), Aruna Subramaniam2, S. Sridevi3, S. Ganesh Kumar4 1Faculty of Allied Health Sciences, Sri Ramachandra Institute of Higher Education, Chennai, Tamil Nadu, India 2Faculty of Nursing, Sri Ramachandra Institute of Higher Education, Chennai, Tamil Nadu, India 3Sri Ramachandra Engineering and Technology, Sri Ramachandra Institute of Higher Education, Chennai, Tamil Nadu, India 4Department of Data Science and Business Systems, School of Computing, SRM Institute of Science and Technology, Kattankulathur, Chennai, Tamil Nadu, India cynthiamilton@ sriramachandra.edu.in https://doi.org/10.3991/ijim.v17i15.41675 https://online-journals.org/index.php/i-jim https://online-journals.org/index.php/i-jim https://doi.org/10.3991/ijim.v17i15.41675 https://doi.org/10.3991/ijim.v17i15.41675 https://online-journals.org/ https://online-journals.org/ mailto:cynthiamilton@sriramachandra.edu.in mailto:cynthiamilton@sriramachandra.edu.in https://doi.org/10.3991/ijim.v17i15.41675 172 International Journal of Interactive Mobile Technologies (iJIM) iJIM | Vol. 17 No. 15 (2023) Milton et al. 1 INTRODUCTION Mobile phones have become the most common device of all digital learning [1]. There is an increase in the number of mobile learning applications due to the enhanced e-learning readiness created among learners after Covid [2]. Mobile learn- ing applications have been effective due to their accessibility from any corner of the world at any time and their interactive features that motivate every learner [3]. Mobile learning (m-learning) applications have proven to be a convenient, ver- satile and effective adjunct and also an alternative to traditional learning methods in nursing education [4]. Many reviews assessing the effectiveness of m-learning applications in enhanc- ing academic and clinical performance of healthcare professionals have proved them to be effective in improving knowledge retention and clinical skills develop- ment and motivation [5, 6 & 7]. A scoping review on nurses adopting m-learning applications shows a favourable and improved clinical performance [8]. Studies highlight that nurses have expressed positive perception towards m-learning and enough conditions to promote nurses’ m-learning should be pro- vided [7, 9]. Further, teaching digital professionalism early in undergraduate nurs- ing curricula and promotion of modelling digitally professional behaviour by nurses within healthcare environments is also imperative [10]. The design of learning and teaching of undergraduate nursing curriculum for Australian healthcare set- tings insists on the need to consider development of policies to support the use of m-learning at point of care [11]. Learner readiness is one of the crucial determiners on implementation of m-learning. A cross-sectional study done among 332 students of medical sciences showed a moderate level of m-learning readiness of the students, which indicated acceptance of m-learning [12]. Mobile-assisted language learning (MALL) is a type of m-learning that uses mobile devices to aid language learning and has high demands among English as Second Language learners to acquire linguistic skills [13]. Android phones are identified as the most popular mobile among MALL mobile platforms [14]. MALLs are developed to provide knowledge on vocabulary, grammar, phonetic practices [15, 16], and can be either general or created to target groups with specific language learning objec- tives under English for specific purpose (ESP) [17, 18]. Nurses’ oral case presentation is a core clinical communication skill with distinc- tive linguistic qualities that contributes to complexity among ESL nurses [19, 20, 21]. The student’s oral case representation is depicted in Table 1. It comprises details of the patient’s personal profile, the past and the present health status and the identi- fied illness and the nursing intervention, which is generally followed by a question session by clinical mentors during clinical postings [22, 23]. Dustyn E Williams [24] points to OCP as an understudied area in nursing teaching curricula. According to C Fang, et al., [25] many ESL student nurses face challenges in OCP due to inadequate grammar, insufficient vocabulary, low listening comprehension, low speaking and pronunciation ability. https://online-journals.org/index.php/i-jim iJIM | Vol. 17 No. 15 (2023) International Journal of Interactive Mobile Technologies (iJIM) 173 Development and Testing of Mobile Assisted Language Learning Application to Improve Oral Clinical Case Presentation of Student Nurses Ta bl e 1. O ra l c as e pr es en ta tio n of st ud en ts N am e of th e In ve st ig at or Ye ar Co nt en t Pr oc ed ur e & A pp ro ac h M ul tim ed ia & T ec hn ol og ic al Fe at ur es (V id eo s/ Gr ap hi cs / So un d/ M us ic / Re so lu tio n Si ze ) O ut co m es St ud y D es ig n Re fe re nc e Ta rg et Le ar ne rs In te re st (G en er al , ES P) Pr ofi ci en cy Le ve l To pi c In st ru ct io na l M at er ia ls Ta sk s (T es t / Q ui z / As se ss m en t) Ba rr et t, 20 22 30 T ai w an es e un de rg ra du at e st ud en ts   Ge ne ra l Ad va nc ed La ng ua ge a nd pr es en ta tio n sk ill s M ul tim ed ia le ar ni ng m at er ia l As se ss m en t En gl ish O ra l Pr es en ta tio n Ap pl ic at io n (E OP A) (R es ea rc he r de ve lo pe d ap p) 37 % o f st ud en ts fo un d EO PA to b e us ef ul fo r l ea rn in g, 33 % ha d so m e di ffi cu lti es us in g th e ap p Fo cu s-g ro up in te rv ie w s  Ba rr et t, N. E ., G . - . L iu , a nd H . - . W an g. “S tu de nt P er ce pt io ns o f a M ob ile L ea rn in g Ap pl ic at io n fo r E ng lis h Or al P re se nt at io ns : Th e Ca se o f E OP A. ” Co m pu te r A ss ist ed L an gu ag e Le ar ni ng , v ol . 3 5, n o. 9 , 2 02 2, pp . 2 47 6– 25 01 . S CO PU S, w w w . sc op us .co m , d oi :1 0. 10 80 /0 95 88 22 1. 20 21 .1 88 19 75 . Zh an g, Y. 20 21 24 im m ig ra tio n offi ce rs a t Do n M ua ng In te rn at io na l Ai rp or t. ES P In te rm ed ia te Or al co m m un ica tiv e le ar ni ng (T w o un its – A rr iv al an d De pa rtu re , an d te n le ss on s t ha t w er e u nd er ea ch u ni t) M at er ia ls de ve lo pe d in AD DI E m od el Ta sk , As se ss m en t ET AI PO (E ng lis h fo r T ha i A irp or t Im m ig ra tio n Po lic e O ffi ce rs – Se lf- in str uc tio na l m at er ia ls) o ffe re d th ro ug h W eC ha t pu bl ic p la tfo rm In str uc tio na l m at er ia ls ha d hi gh q ua lit y of co nt en t, ra tio na l or ga ni za tio n, pl ea sa nt pr es en ta tio n an d co nv en ie nt fu nc tio ns o f th e p la tfo rm . As se ss m en t Zh an g, Y. (2 02 1) . A de ve lo pm en t o f M AL L m at er ia ls to q ua lit y ed uc at io n an d su pp or t E ng lis h or al co m m un ic at iv e le ar ni ng o f Th ai a irp or t i m m ig ra tio n po lic e offi ce rs . P ap er pr es en te d at th e  E3 S W eb o f Co nf er en ce s,  29 5  do i:1 0. 10 51 / e3 sc on f/2 02 12 95 05 02 9 Re tr ie ve d fr om  w w w . sc op us .co m Ka ss em 20 18 EF L Te ac he r Tr ai ne es of A ss iu t Un iv er sit y, Eg yp t Ge ne ra l Ad va nc ed Vo ca bu la ry ac qu isi tio n In tr od uc tio n an d fo ur u ni ts on v oc ab ul ar y. Qu iz 4 vo ca bu la ry le ar ni ng ap pl ic at io ns : • Qu iz le t • Di gi ta l Vo ca bu la ry No te bo ok • Di gi ta l V id eo Ga m es On lin e Di ct io na rie s im pr ov em en t in v oc ab ul ar y ac qu isi tio n, en ha nc ed m ot iv at io n pe rc ep tio ns Pr e an d Po st T es t Ka ss em , M oh am ed A li M oh am ed . “ Th e eff ec t of a su gg es te d in -se rv ic e te ac he r t ra in in g pr og ra m ba se d on M AL L ap pl ic at io ns on d ev el op in g EF L st ud en ts ’ v oc ab ul ar y ac qu isi tio n. ” J ou rn al o f La ng ua ge T ea ch in g an d Re se ar ch  9 .2 (2 01 8) : 2 50 –2 60 . (C on tin ue d) https://online-journals.org/index.php/i-jim http://www.scopus.com http://www.scopus.com http://doi.org/10.1080/09588221.2021.1881975 http://doi.org/10.1051/e3sconf/202129505029 http://doi.org/10.1051/e3sconf/202129505029 http://www.scopus.com/ http://www.scopus.com/ 174 International Journal of Interactive Mobile Technologies (iJIM) iJIM | Vol. 17 No. 15 (2023) Milton et al. Ta bl e 1. O ra l c as e pr es en ta tio n of st ud en ts (C on tin ue d) N am e of th e In ve st ig at or Ye ar Co nt en t Pr oc ed ur e & A pp ro ac h M ul tim ed ia & T ec hn ol og ic al Fe at ur es (V id eo s/ Gr ap hi cs / So un d/ M us ic / Re so lu tio n Si ze ) O ut co m es St ud y D es ig n Re fe re nc e Ta rg et Le ar ne rs In te re st (G en er al , ES P) Pr ofi ci en cy Le ve l To pi c In st ru ct io na l M at er ia ls Ta sk s (T es t / Q ui z / As se ss m en t) M or en o 20 15 16 S pa ni sh Er as m us st ud en ts a t t he de pa rt m en t o f Tr an sla tio n, Ge ne ra l In te rm ed ia te Or al S ki lls Co m m un ic at iv e ap pr oa ch , Ta sk b as ed ap pr oa ch An al ys is of th e tra ns cr ip tio ns of th e pa rt ic ip an ts ’ re co rd in gs VI SP (V id eo s fo r S pe ak in g) is a M AL L ap p de ve lo pe d by m em be rs o f t he UN ED -b as ed A TL AS re se ar ch g ro up an d th e Gh en t Un iv er sit y- ba se d GO LL D re se ar ch gr ou p to p ro m ot e or al p ra ct ic e in E ng lis h. Im pr ov ed ac cu ra cy in vo ca bu la ry us ag e Pr e an d po st qu es tio nn ai re M or en o, A na Ib áñ ez , a nd An na V er m eu le n. “U sin g VI SP (V id eo s f or S pe ak in g) , a m ob ile A pp b as ed o n Au di o De sc rip tio n, to p ro m ot e En gl ish La ng ua ge L ea rn in g am on g Sp an ish S tu de nt s: a ca se st ud y.”  P ro ce di a- So ci al a nd Be ha vi or al S ci en ce s  17 8 (2 01 5) : 1 32 –1 38 . Qu n W u  20 15 Ch in es e co lle ge st ud en ts of Ji nj ia ng Un iv er sit y Ge ne ra l In te rm ed ia te CE T4 - En gl ish (L 2) vo ca bu la ry – sp el lin g, pr on un ci at io n an d Ch in es e de fin iti on s.  Re se ar ch er de sig ne d W or d Le ar ni ng co nt en t Tu to ria ls an d dr ill W or d Le ar ni ng - CE T4 A pp lic at io n (R es ea rc he r de ve lo pe d ap p) Ba sic 4A nd ro id (B 4A ), ve ry sim ila r t o Vi su al Ba sic , i s a si m pl e pr og ra m m in g la ng ua ge  w ith To uc hs cr ee n w ith co m m an ds , a B4 A ap pl ic at io n w ith to uc hs cr ee n Im pr ov ed vo ca bu la ry ac qu isi tio n Pr e an d Po st T es t W u, Q un . “ Pu lli ng m ob ile as sis te d la ng ua ge le ar ni ng (M AL L) in to th e m ai ns tr ea m : M AL L in b ro ad p ra ct ic e.”  P lo S on e  10 .5 (2 01 5) : e 01 28 76 2. https://online-journals.org/index.php/i-jim iJIM | Vol. 17 No. 15 (2023) International Journal of Interactive Mobile Technologies (iJIM) 175 Development and Testing of Mobile Assisted Language Learning Application to Improve Oral Clinical Case Presentation of Student Nurses Generally, OCP skill is developed through observation while inadequate language preparation is one of the OCP challenges of ESL nursing graduates [22, 26]. Presently, there aren’t any OCP MALL apps that are available for ESL nurses. Although m-learning applications that help to develop knowledge on OCP skills such as decision making are available, still most of them aren’t primarily for language enhancement. However, many of these are meant for novice doctors [27, 28] and so the content significantly differs from nursing practice. Considering these deficits, the present OCP MALL application was developed and imple- mented to provide English language training to improve Oral Case Presentation of student nurses pursuing baccalaureate degrees from South Indian University. 2 REVIEW OF LITERATURE Studies related to effectiveness of MALL applications show a positive acceptance of mobile techniques [29], a complementary method [30], higher scores on tests, increased motivation, interest, and confidence after four consecutive weeks of inter- vention [31, 32]. Studies integrating m-learning in nursing education showed better academic achievements and satisfaction [33], positive students’ attitudes, students’ satisfaction, and students’ academic achievements [6]. 2.1 Phase 1 – OCP mall development A. Instructional Module The OCP MALL instructional module was developed in the ADDIE model based on language and learning theories and principles to develop the materials which comes with five phases: analysis, design, development, implementation, and evalua- tion. As readily available English language training modules for OCP were not avail- able, the content was prepared through review of literature on genre analysis of medical case reports. The structural move analysis [34] to understand the character- ization of organizational and textual patterns and the lexico-grammatical structure [35] typical to the medical discourse were identified. Based on the review, the learn- ing content framework was designed as per SOAP (Subjective, Objective, Assessment and Plan) [36] format, a highly structured format for delivering the health details of patients. The entire learning content was organized into small learnable chunks of digestible bits of information, with clear learning objectives and asynchronous learner-controlled instructional materials. A landing page consisting of characteris- tics, structural moves and barriers of OCP followed by five levels of learning content on grammar and vocabulary and quiz at each level (Figure 1) was developed. https://online-journals.org/index.php/i-jim 176 International Journal of Interactive Mobile Technologies (iJIM) iJIM | Vol. 17 No. 15 (2023) Milton et al. Fig. 1. OCP MALL pipeline B. Integration of Multimedia Digital tools such as Screencast o’matic, Free Cam (Screen Capturing) for video making, render forest app (free animation tool) and note vibes (for conversion of plain text to digital format graphics) and free music (from https://www.bensound.com) were integrated to add digital effects and make videos is mentioned in Figure 2. Fig. 2. Screenshots of the videos https://online-journals.org/index.php/i-jim https://www.bensound.com/ iJIM | Vol. 17 No. 15 (2023) International Journal of Interactive Mobile Technologies (iJIM) 177 Development and Testing of Mobile Assisted Language Learning Application to Improve Oral Clinical Case Presentation of Student Nurses C. Technical Features i. Technology Stack  The application was developed as a Progressive Web App using modern open-source frameworks listed below. UI - React CMS - Strapi Database - Postgres Cross Platform - Ionic Framework  The following features were introduced in the development of OCP MALL app. ii. Course overview  The course overview screen was provided for learners who are taking the course for viewing important information. It introduced the main idea of the course describing the topics or concepts that the course covers. Home Page – Course – Overview iii. App navigation  The navigation feature allowing users to navigate across, into, and back out from the different pieces of content within the app was introduced. https://online-journals.org/index.php/i-jim 178 International Journal of Interactive Mobile Technologies (iJIM) iJIM | Vol. 17 No. 15 (2023) Milton et al. Navigator iv. Level based progression  A description of increasing levels of difficulty and complexity in acquiring knowledge, skills and attitudes within a domain. It implies that learning is a process of increasing difficulty and complexity, rather than a body of content to be covered within specific grade levels. Learning levels https://online-journals.org/index.php/i-jim iJIM | Vol. 17 No. 15 (2023) International Journal of Interactive Mobile Technologies (iJIM) 179 Development and Testing of Mobile Assisted Language Learning Application to Improve Oral Clinical Case Presentation of Student Nurses v. Dynamic content management  A Learning Content Management System (LCMS) is  a platform that inte- grates authoring, delivery, publishing and analysis of content in a multi-user environment. In our LCMS definition, it provides content professionals a way to manage their content and collaborate in one centralized location. vi. Quiz based assessment  A quiz is a quick and informal assessment of student knowledge. So, at every level following each learning content, a quiz was introduced vii. Performance tracking  Mobile application performance monitoring is the tracking of key app per- formance indicators in order to maintain awareness of your app’s perfor- mance and potential quality issues. viii. Retake of quiz to improvise performance  Allowing students to retake any quizzes where they don’t achieve a perfect score. A “Restart Quiz” button is displayed after each quiz. During a retake, students are only presented with questions they answered incorrectly on the previous attempt. Assessment Score ix. Progression reporting  A progress report is  a report which updates information about the learn- ing to the learners. Progress reports make it possible for learners to change or improve their performance. Here the students’ level of progress could be tracked through the change in the colour of the heading caption from grey to black. https://online-journals.org/index.php/i-jim 180 International Journal of Interactive Mobile Technologies (iJIM) iJIM | Vol. 17 No. 15 (2023) Milton et al. Change in font colour x. Suitable for Android phone  The app was developed suitable for Android phone. D. Alpha Test Alpha testing was carried out with research team members. The OCP-MALL application was downloaded and tested for all the features of the application. In case any errors occurred during the testing phase, it was reported to the mobile app developers after rectification of the errors and retesting again with team members. E. Beta Test In the development process of the OCP-MALL, beta testing was carried out with 13 nursing students from the BSc Nursing (Post Basic) Programme. The researcher insisted the end users use all the features of the application. The end users used the application in a real-time environment and provided feedback about the appli- cation. In case any error occurred in the testing phase, the end users reported it to the researcher. The researcher reported to one of the researchers doing mobile application development to rectify the errors. The researcher asked end users to give feedback on the applications. Using this feedback, mobile developers further improve the application. 2.2 Phase – 2 OCP-mall feasibility a. Study Design A pre and post-test design was used for the study. https://online-journals.org/index.php/i-jim iJIM | Vol. 17 No. 15 (2023) International Journal of Interactive Mobile Technologies (iJIM) 181 Development and Testing of Mobile Assisted Language Learning Application to Improve Oral Clinical Case Presentation of Student Nurses b. Participant Selection and Sample Size The sample size was calculated using the OpenEpi menu considering the primary outcome variable as confidence and based on previous study done by Jenny Lee [37]. Based on confidence mean (mean1 = 28.78, mean2 = 25.77) and standard devia- tion (S1 = 5, S2 = 3.42) 40, considering attrition, the average sample size 60 was taken into consideration. The participants consist of 62 nursing graduates from the 2nd year of B. Sc Nursing programme from a reputed nursing college in Chennai, South India, under- going clinical posting, using an Android mobile phone and willing to participate. c. Methodology i. Pre-Test: The pre-test included a published standardized self-plotting tool [38] to capture the perceived language difficulty in explaining the case in English. It con- sists of 16 language difficulty statements which addressed the perceived level of difficulty in explaining the cases (OCP) in English, use of nursing terms, grammat- ical errors and especially the tense mistakes, asking and answering questions. ii. App Usage: OCP-MALL application was hosted from a local server. The link of the app was shared with the participants through e-mail. Access was given to the par- ticipants who enrolled using the link and the user manual was shared through e-mail. The users were given a four-week time period to complete the practice of learning using samples in the OCP-MALL app. A WhatsApp group was created with all the participants and reminders were sent. iii. Post Test: At the end of the assigned period and another round of post assess- ments, the following were identified (1) User feedback on acceptance of OCP- MALL, (2) Perceived language difficulty in explaining the case in English. Along with these, (3) A comparison of the real time ward performance practical marks were given by the nursing mentors before and after the practice using OCP-MALL was completed. 3 RESULTS 3.1 Descriptive statistics Table 2. Demographic details of the participants S. No Variables (No. 62) % 1 Gender Female 46  74 Male 16  26 2 Age 17–20 62 100 21–23  0  0 3 Type of Mobile in use Android 61  98 Apple IOS  1  2 The demographic details showed that most of them were female student nurses (74%) from the age group of 17 to 20 (100%) and using an Android type of mobile phone (98%). https://online-journals.org/index.php/i-jim 182 International Journal of Interactive Mobile Technologies (iJIM) iJIM | Vol. 17 No. 15 (2023) Milton et al. 3.2 User acceptance The efficacy of the OCP app was tested for the level of user acceptance of OCP- MALL. A semi-structured questionnaire constructed based on literature review on the participant’s experience, their level of satisfaction and acceptance of the OCP- MALL performance was used to elicit the participants’ response. The details are rep- resented in Table 3. Table 3. User feedback on ocp mobile app functionality Items Minimum Maximum Mean Std. Deviation Login with ease 2 10 7.99 1.620 Clarity in reading the text – Clear font size (caption, texts, and typography)- 4 10 8.29 1.276 Clarity in text layout 3 10 8.14 1.497 Clarity in audio 5 10 8.03 1.464 Smooth running of audio without troubleshooting 3 10 7.91 1.567 Clarity in video 4 10 8.04 1.536 Smooth running of video without troubleshooting 2 10 7.77 1.617 Easiness in attempting quiz 4 10 8.06 1.483 Simplicity in navigation – Scrolling the page 3 10 8.06 1.531 Simplicity in navigation – moving to next page 4 10 8.19 1.526 Resuming your task during your next login. 4 10 7.96 1.583 User friendliness of the application 4 10 8.13 1.393 Privacy and security issues of the application 2 10 7.80 1.708 TOTAL 47.00 120.00 96.3286 14.74294 In this study, the operational definition for acceptability for each item was assumed as the mean score of app usability ≥70%, derived from the m-learning application acceptance questionnaire developed by the researcher. The scale has 12 items, with each scored on a 10-point Likert scale (1 = strongly disagree; 10 = strongly agree). Higher scores identified a greater perception of usability. A score of ≥7 was considered to have good usability Upon completion of OCP app usage, all 62 participants filled the questionnaire. Participants rated the clarity in reading the text with highest mean score of 8.29 and std of 1.276, simplicity in navigation - moving to next page with next highest mean score of 8.19 and std of 1.526, clarity in text application layout with a mean score of 8.14 and std of 1.497 and user-friendliness of the application with a mean score of 8.13 and std of 1.393. More details are presented in Table 3. https://online-journals.org/index.php/i-jim iJIM | Vol. 17 No. 15 (2023) International Journal of Interactive Mobile Technologies (iJIM) 183 Development and Testing of Mobile Assisted Language Learning Application to Improve Oral Clinical Case Presentation of Student Nurses 3.3 Comparison of perceived language difficulty in explaining the case in English Table 4. Comparison of the pre and post test levels of perceived language difficulty in explaining the case in English Item Pre Post Mean Difference Z-Value P- Value Mean S.D Mean S.D Inability to fluently present OCP in English 4.96 0.209 2 0.798 2.96 4.13 0.0005 Difficult to explain the case handling procedures in English 4.96 0.209 2.09 0.668 2.87 4.26 0.0005 Inability to comprehend Mentors instruction in English 4.3 1.259 1.96 0.825 2.34 3.93 0.0005 Giving excuses for not answering in English 4.96 0.209 2.17 0.778 2.79 3.76 0.0005 Difficulty pronouncing nursing terms. 4.43 0.945 2.17 1.072 2.26 4.31 0.0005 Hesitation to use any new word/Terms 4.83 0.388 2 1 2.83 3.95 0.0005 Making many grammatical errors while presenting OCP in English 4.43 0.896 2.09 0.949 2.34 4.06 0.0005 Difficulty to understand the questions asked in English during OCP. 4.83 0.388 2.14 0.774 2.69 4.26 0.0005 Inability to answer in English for the questions 4.35 1.027 2.39 1.033 1.96 4.13 0.0005 Difficulty to understand the meaning of the words which I use in my OCP 4.87 0.344 2.39 0.941 2.48 4.34 0.0005 Memorizing the lines in my OCP 3.91 1.311 1.91 0.996 1 4.01 0.0005 Knowing very less of English words 4.87 0.344 2.09 1.203 2.78 4.23 0.0005 Lack fluency to present OCP in English 3.33 1.091 1.87 0.785 1.46 –5.417b 0.0005 Difficulty to clarify doubts. 3.87 1.103 1.77 0.902 2.1 –6.267b 0.0005 Not knowing how to correct my grammar mistakes that I make. 4. 1.033 1.75 0.699 2.25 –6.301b 0.0005 Not knowing how to use different tenses in my OCP 4.08 0.971 1.66 0.75 2.42 –6.514b 0.0005 The above Table 4 presents pre- and post-test analysis of the perceived changes in the language difficulties of student nurses in performing OCP in English. The find- ings show that all of aspects of the identified language difficulty have decreased in significant ways after the participants had undergone the practice using OCP-MALL. The overall pre-test and post-test analysis pertaining to language difficulty shows that the highest perceived change was seen in the use of tenses (Q 16) which had https://online-journals.org/index.php/i-jim 184 International Journal of Interactive Mobile Technologies (iJIM) iJIM | Vol. 17 No. 15 (2023) Milton et al. a mean difference of 2.42; applying grammar concepts in OCP (Q-15) had a mean difference of 2.25. Similarly, a significant change was also found in confidence to build fluency needed to carry out OCP (Q-1), which had a mean difference of 2.96; explaining the procedure (Q-2) showed a mean difference of 2.87; ability to clear doubts (Q-3) had a mean difference of 2.34; decrease in the practice of memorizing (Q-11) had a mean difference of 1. Next to these, the perceived changes were in the use of vocabulary with a mean increase of 2.78 in lexical skill (Q-12). 3.4 Comparison of OCP practical marks Table 5. Inferential statistical analysis of the clinical presentation scores Variable Mean N Std. Deviation MeanDifference T-Value P-Value P 1 62.79 62 7.541 –5.574 –6.095 .000 P 2 68.36 62 7.893 Table 5 represents the comparison of second year Medical Nursing OCP practical marks with Surgical Nursing CP practical marks. The analysis found a significant change in the mean score of P1 with P2 with a moderate increase, which could be interpreted as a gradual betterment over time. 4 DISCUSSION The content of the present OCP-MALL has been designed using the well-accepted ADDIE model base. Berking P, Haag J, Archibald [39] recommend the ADDIE model to be the most generic, universal, and simple one that can be adopted into m-learning. With regard to the technical features, the present mobile application developed is a start up with all essential basic features. However, on comparison with native applications, some of the advanced multimedia features of native applications could be missing. Yet, these differences were not pointed out by the participants in their feedback on application acceptance. This could be attributed to the fact that the participants could have perceived it beneficial as this is the first-of-its-kind applica- tion to learn English required for improving OCP skills. Likewise, in the sequential grouping of learning content being based on the SOAP format, which is the generally recommended and familiar structure for all student nursing case presentation prac- tice, no contradictions or deviations in their regular case presentation styles were observed. The overall effectiveness is reflected in their significant change noted in the real time performance score and perceived language difficulty (P ≤ 0.05). Similar effectiveness was observed in the study by Al-Fahad FN [40] among graduates from a Saudi Arabian university which liberated m-learning. The findings showed that students learnt more easily when information was divided into small learnable amounts to enable effective micro-learning. A good cloud infrastructure is required for the deployment of applications from a remote mode. This requires a constant financial backing that could lead to finan- cial constraints for novice start-up application designers unless it is commercialised. Verma K, Dubey S, Rizvi M [41] proposes details on how cloud-based m-learning can https://online-journals.org/index.php/i-jim iJIM | Vol. 17 No. 15 (2023) International Journal of Interactive Mobile Technologies (iJIM) 185 Development and Testing of Mobile Assisted Language Learning Application to Improve Oral Clinical Case Presentation of Student Nurses make use of local resource opportunities available in higher education institutions that can be used effectively to implement and enhance m- learning. 5 CONCLUSION Experience is the best teacher which can offer great learning opportunities to acquire new skills. The researcher, understanding the demand for m-learning appli- cations, has attempted to identify a specific clinical communication task of student nurses. The researcher has also gained hands-on experience in developing e-content, designing the framework for mobile applications. The researcher has also checked the feasibility and user feedback of this cost-effective mobile application. Ethical Consideration: Ethical clearance approval for the conduct of study was obtained from the Institutional Ethics Committee of a deemed university attached to a teaching hospital which runs nursing programmes with a nursing students’ strength of 1400 (Ref. No. IEC‐NI/21/FEB/77/14). Acknowledgement: The present study was funded and done under the institu- tional GATE project. 6 REFERENCES [1] El-Sofany, H. F., & El-Haggar, N. (2020). The effectiveness of using mobile learning techniques to improve learning outcomes in higher education. International Journal of Interactive Mobile Technologies, 14(8), 4–18. https://doi.org/10.3991/ijim.v14i08.13125 [2] Agu, C. F., Stewart, J., McFarlane-Stewart, N., & Rae, T. (2021). COVID-19 pandemic effects on nursing education: Looking through the lens of a developing country. International Nursing Review, 68(2), 153–158. https://doi.org/10.1111/inr.12663 [3] Kumar Basak, S., Wotto, M., & Bélanger, P. (2018). E-learning, M-learning and D-learning: Conceptual definition and comparative analysis. E-Learning and Digital Media, 15(4), 191–216. https://doi.org/10.1177/2042753018785180 [4] O’Connor, S., & Andrews, T. (2018). Smartphones and mobile applications (apps) in clinical nursing education: A student perspective. Nurse Education Today, 69, 172–178. https://doi.org/10.1016/j.nedt.2018.07.013 [5] Chandran, V. P., Balakrishnan, A., Rashid, M., Pai Kulyadi, G., Khan, S., Devi, E. S., Nair, S., & Thunga, G. (2022). Mobile applications in medical education: A systematic review and meta-analysis. PLOS ONE, 17(3), e0265927. https://doi.org/10.1371/journal.pone.0265927 [6] Salameh, B., Ewais, A., & Salameh, O. (2020). Integrating M-learning in teaching ECG reading and arrhythmia management for undergraduate nursing students. International Journal of Interactive Mobile Technologies, 14(1), 82–95. https://doi.org/10.3991/ijim. v14i01.11417 [7] Xiao, Q., Sun, A., Wang, Y., Zhang, Y., & Wu, Y. (2018). Nurses’ experiences and percep- tions of mobile learning: A survey in Beijing, China. Stud Health Technol Inform, 250, 86–87. PMID: 29857391. [8] Nezamdoust, S., Abdekhoda, M., Ranjbaran, F., & Azami-Aghdash, S. (2022). Adopting mobile health applications by nurses: A scoping review. J Res Nurs. 27(5), 480–491. Epub 2022 Jul 4. PMID: 36131693; PMCID: PMC9483232. https://doi. org/10.1177/17449871221077080 [9] Garrison, E., Colin, S., Lemberger, O., & Lugod, M. (2021). Interactive learning for nurses through gamification. J Nurs Adm. 51(2), 95–100. PMID: 33449599. https://doi. org/10.1097/NNA.0000000000000976 https://online-journals.org/index.php/i-jim https://doi.org/10.3991/ijim.v14i08.13125 https://doi.org/10.1111/inr.12663 https://doi.org/10.1177/2042753018785180 https://doi.org/10.1016/j.nedt.2018.07.013 https://doi.org/10.1371/journal.pone.0265927 https://doi.org/10.3991/ijim.v14i01.11417 https://doi.org/10.3991/ijim.v14i01.11417 https://doi.org/10.1177/17449871221077080 https://doi.org/10.1177/17449871221077080 https://doi.org/10.1097/NNA.0000000000000976 https://doi.org/10.1097/NNA.0000000000000976 186 International Journal of Interactive Mobile Technologies (iJIM) iJIM | Vol. 17 No. 15 (2023) Milton et al. [10] Mather, C., Cummings, E., & Gale, F. (2018). Mobile learning in nursing: Tales from the profession. Stud Health Technol Inform, 252, 112–117. PMID: 30040692. [11] Mather, C., & Cummings, E. (2015). Unveiling the mobile learning paradox. Stud Health Technol Inform., 218, 126–131. PMID: 26262539. [12] Azizi, S. M., & Khatony, A. (2019). Investigating factors affecting on medical sciences stu- dents’ intention to adopt mobile learning. BMC Med Educ, 19, 381. https://doi.org/10.1186/ s12909-019-1831-4 [13] Abu Sa’aleek, & Atef Odeh. (2014). A review of emerging technologies: Mobile assisted language learning (MALL). Asian Journal of Education and E-learning, 2(6). [14] Pocatilu, & Paul. (2010). Developing mobile learning applications for Android using web services. Informatica Economica, 14(3), 106. [15] Duman, Guler, Gunseli Orhon, & Nuray Gedik. (2015). Research trends in mobile assisted language learning from 2000 to 2012. ReCALL, 27(2), 197–216. https://doi.org/10.1017/ S0958344014000287 [16] Viberg, Olga, & Åke Grönlund. (2012). Mobile assisted language learning: A literature review. 11th World Conference on Mobile and Contextual Learning. [17] Kassem, & Mohamed Ali Mohamed. (2018). The effect of a suggested in-service teacher training program based on MALL applications on developing EFL students’ vocabu- lary acquisition. Journal of Language Teaching and Research, 9(2), 250–260. https://doi. org/10.17507/jltr.0902.05 [18] Zhang, Y. (2021). A development of MALL materials to quality education and support English oral communicative learning of Thai airport immigration police officers. Paper presented at the E3S Web of Conferences, 295. Retrieved from www.scopus.com; https:// doi.org/10.1051/e3sconf/202129505029 [19] Anspach, R. R. (1988). Notes on the sociology of medical discourse: The language of case presentation. Journal of Health and Social Behavior, 29(4), 357–375. Available from https:// deepblue.lib.umich.edu/bitstream/handle/2027.42/51147/379.pdf?sequence=1&isAl- lowed=y; https://doi.org/10.2307/2136869 [20] Prasetyanti, & Widya. (2014). Case study: Encouraging nurses to develop skills and con- fidence in Indonesia. Community eye health, 27(86), 33. [21] Richard J. Haber, & Lorelei A. Lingard. (2001). Learning oral presentation skills: A rhe- torical analysis with pedagogical and professional implications. J Gen Intern Med. 16(5), 308–314. Available from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1495213; https://doi.org/10.1046/j.1525-1497.2001.00233.x [22] Milton, Cynthia, & Prabakaran, M. (2020). Need and relevance for English language training in oral case presentation of student nurses. Indian Journal of Continuing Nursing Education, 21(2), 135. https://doi.org/10.4103/IJCN.IJCN_20_19 [23] Mei Yuit Chan. (2015). The oral case presentation: Toward a performance-based rhe- torical model for teaching and learning. Medical Education Online, 20(1). https://doi. org/10.3402/meo.v20.28565 [24] Dustyn E. Williams, Shravani Surakanti, & Ochsner, J. (2016). Developing oral case pre- sentation skills: Peer and self-evaluations as instructional tools. Spring, 16(1), 65–69. Available from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4795506/ [25] Fang, C. Tsai, C., & Huang. (2011). Needs and barriers in ESP education: Exploring the preference in ESL nursing students, Proc. International Symposium on ESP and Its Application in Nursing & Stylistic Features Medical English Education, Taiwan. [26] Nirmala, V., & Suni, M. S. (2022). Language related difficulties experienced by student nurses. International Journal of Psychiatric Nursing, 8(2), 12–15. https://doi.org/10.37506/ ijpn.v8i2.18231 [27] MyMedicalTutor app allows doctors to practice presentation skills (imedicalapps.com) [28] MedShr: Discuss Clinical Cases – Apps on Google Play https://online-journals.org/index.php/i-jim https://doi.org/10.1186/s12909-019-1831-4 https://doi.org/10.1186/s12909-019-1831-4 https://doi.org/10.1017/S0958344014000287 https://doi.org/10.1017/S0958344014000287 https://doi.org/10.17507/jltr.0902.05 https://doi.org/10.17507/jltr.0902.05 http://www.scopus.com https://doi.org/10.1051/e3sconf/202129505029 https://doi.org/10.1051/e3sconf/202129505029 https://deepblue.lib.umich.edu/bitstream/handle/2027.42/51147/379.pdf?sequence=1&isAllowed=y https://deepblue.lib.umich.edu/bitstream/handle/2027.42/51147/379.pdf?sequence=1&isAllowed=y https://deepblue.lib.umich.edu/bitstream/handle/2027.42/51147/379.pdf?sequence=1&isAllowed=y https://doi.org/10.2307/2136869 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1495213 https://doi.org/10.1046/j.1525-1497.2001.00233.x https://doi.org/10.4103/IJCN.IJCN_20_19 https://doi.org/10.3402/meo.v20.28565 https://doi.org/10.3402/meo.v20.28565 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4795506/ https://doi.org/10.37506/ijpn.v8i2.18231 https://doi.org/10.37506/ijpn.v8i2.18231 iJIM | Vol. 17 No. 15 (2023) International Journal of Interactive Mobile Technologies (iJIM) 187 Development and Testing of Mobile Assisted Language Learning Application to Improve Oral Clinical Case Presentation of Student Nurses [29] El-Sofany, Hosam, & Nahla El-Haggar. (2020). The effectiveness of using mobile learning techniques to improve learning outcomes in higher education, 14(8), 4–18. https://doi. org/10.3991/ijim.v14i08.13125 [30] Hao, Y., Lee, K. S., Chen, S. T., & Sim, S. C. (2019). An evaluative study of a mobile applica- tion for middle school students struggling with English vocabulary learning. Computers in Human Behavior, 95, 208–216. https://doi.org/10.1016/j.chb.2018.10.013 [31] Chee, Ken Nee, Noraffandy Yahaya, & Nor Hasniza Ibrahim. (2017). Effectiveness of mobile learning application in improving reading skills in Chinese language and towards post-attitudes. International Journal of Mobile Learning and Organisation, 11(3), 210–225. https://doi.org/10.1504/IJMLO.2017.085347 [32] Loewen, S., Crowther, D., Isbell, D. R., Kim, K. M., Maloney, J., Miller, Z. F., & Rawal, H. (2019). Mobile-assisted language learning: A Duolingo case study.  ReCALL,  31(3), 293–311. https://doi.org/10.1017/S0958344019000065 [33] Kenny, R. F., Van Neste-Kenny, J. M., Burton, P., Park, C. L., & Qayyum, A. (2012). Using self-efficacy to assess the readiness of nursing educators and students for mobile learn- ing.  International Review of Research in Open and Distributed Learning,  13(3), 277–296. https://doi.org/10.19173/irrodl.v13i3.1221 [34] Robert Helán. (2012). Analysis of published medical case reports: Genre-based study. Available from https://is.muni.cz/th/18899/ff_d/DISSERTATION_-_ROBERT_HELAN.pdf [35] Yuliia  Lysanets, Halyna  Morokhovets, & Olena  Bieliaieva. (2017). Stylistic features of case reports as a genre of medical discourse. Journal of Medical Case, 83.   Available from  https://jmedicalcasereports.biomedcentral.com/articles/10.1186/s13256-017-1247; https://doi.org/10.1186/s13256-017-1247-x [36] Brown, L. H. (2006). The case presentation as argument. Journal of the American Association of Nurse Practitioners, 18(9), 395–396. https://doi.org/10.1111/j.1745-7599.2006.00155.x [37] Lee, N. J., Chae, S. M., Kim, H., Lee, J. H., Min, H. J., & Park, D. E. (2016). Mobile- based video learning outcomes in clinical nursing skill education: A randomized controlled trial.  Computers, Informatics, Nursing,  34(1), 8. https://doi.org/10.1097/ CIN.0000000000000183 [38] Premalatha, & Cynthia, V . (2017). Development of self-assessment tool to determine language difficulty and its associated psychological barriers in presenting clinical cases among student nurses with limited English proficiency (LEP) (June 7, 2018). The IUP Journal of English Studies, XII(1), 51–57, Available at SSRN:  https://ssrn.com/ abstract=3192296 [39] Berking, P., Haag, J., Archibald, T., & Birtwhistle, M. (2012). Mobile learning: Not just another delivery method. In Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC), 1–30. [40] Al-Fahad, F. N. (2009). Students’ attitudes and perceptions towards the effectiveness of mobile learning in King Saud University, Saudi Arabia. Online Submission, 8(2). [41] Verma, K., Dubey, S., & Rizvi, M. (2012). Mobile cloud a new vehicle for learning: M-learning its issues and challenges. International Journal of Science and Applied Information Technology, 1(3). 7 AUTHORS Dr. Cynthia Milton is presently working as an assistant professor in English at Sri Ramachandra Institute of Higher Education and Research, Chennai, India. She has about nineteen years of English language teaching experience for the paramed- ical programs including nursing. Serving a medical university has given her the wonderful opportunity to explore the language needs of various medical profes- sional groups and construct appropriate English learning curriculum to match their https://online-journals.org/index.php/i-jim https://doi.org/10.3991/ijim.v14i08.13125 https://doi.org/10.3991/ijim.v14i08.13125 https://doi.org/10.1016/j.chb.2018.10.013 https://doi.org/10.1504/IJMLO.2017.085347 https://doi.org/10.1017/S0958344019000065 https://doi.org/10.19173/irrodl.v13i3.1221 https://is.muni.cz/th/18899/ff_d/DISSERTATION_-_ROBERT_HELAN.pdf https://jmedicalcasereports.biomedcentral.com/articles/10.1186/s13256-017-1247 https://doi.org/10.1186/s13256-017-1247-x https://doi.org/10.1111/j.1745-7599.2006.00155.x https://doi.org/10.1097/CIN.0000000000000183 https://doi.org/10.1097/CIN.0000000000000183 https://ssrn.com/abstract=3192296 https://ssrn.com/abstract=3192296 188 International Journal of Interactive Mobile Technologies (iJIM) iJIM | Vol. 17 No. 15 (2023) Milton et al. needs. She holds a doctorate degree in English with a special focus on enriching nurses’ clinical communication. The present study is a projection of her research work. She has over 6 publications in peer reviewed indexed journals. She has served as an education unit member for more than 4 years and is now the secretary of it. She is also an active member of her university Curriculum Committee and an editor of the College newsletter. She has organized many special English language support training programmes to help students and faculty. She has great passion in bring excellence in the field of Education. Dr. Aruna Subramaniam is presently working as a Professor and head of the community health nursing department at Sri Ramachandra Faculty of Nursing, Sri Ramachandra Institute of Higher Education and Research (DU), Chennai, India. She has about 25 years of teaching experience in nursing. She holds a doctorate degree in nursing with a special focus on adolescent’s health. The present study is a projection of her research work. She has over 16 publications in peer reviewed indexed journals. She has served as a nursing education unit and university internal assessment cell member and member secretary of the Institutional Ethics commit- tee of the Sri Ramachandra Institute of Higher Education & Research – Institutional Ethics Committee – (Students for UG & Non-Medical PG). Has interest in collabora- tive research work for the best Evidence Based Practice in the field of “Community Health Nursing” and “Maternal and Child Health Nursing”. Has passion in the fields of diabetes, hypertension, yoga and reproductive health, guiding undergraduate, postgraduate for more than 15 years and doctoral students for more than 8 years (E-mail: aruna.s@sriramachandra.edu.in). Dr. S. Sridevi is presently working as an Assistant Professor, CSE, at Sri Ramachandra Engineering and Technology for the past 1 year. She has been in aca- demics and research for the past 15 years. She received a B.E degree in Computer Science Engineering from the University of Madras, finished M.E degree in Computer Science Engineering from Anna University and Ph.D. degree from Vels Institute of Science and Technology Advanced Studies [VISTAS]. Her main research interests are in the areas of Wireless Communications, Networking, WSN, AI, Machine Learning, Deep Learning, and its applications. She has published more than 35 research papers in Scopus, UGC, and Google Scholar. And also presented research papers at 10 National and 12 International conferences. I filed the three patents and published the two book chapters (E-mail: sridevi@sret.edu.in). Dr. S. Ganesh Kumar is presently working as a Professor, Department of Data Science and Business Systems, School of Computing at SRMIST for the past 20 years. He has been in academics and research for the past 15 years. His specialized research  area is in Cloud computing, Block chain Technology, SOA, Web services and Internet of things. He has presented around 35 research papers in national and international conferences and more than 30 research articles published in refereed journals. He has been a technical chair in different national and international con- ferences in India and abroad. He was a member in the review committee, Advisory committee, and Technical committee for international conferences and refereed journals (E-mail: ganeshk1@srmist.edu.in). https://online-journals.org/index.php/i-jim mailto:aruna.s@sriramachandra.edu.in mailto:sridevi@sret.edu.in mailto:ganeshk1@srmist.edu.in