New designs of 6-year undergraduate medical education (UME) in Taiwan mainly include (1) integral curricula of body organ system, (2) multiple methods of clinical teaching and assessment, and (3) generalism in UME. Accompany with decreasing educational hours in the classrooms and hospital, essential but minor components of primary healthcare such as ophthalmology and otolaryngology-head and neck surgery (ORL-HNS) is disproportionately under-represented in UME. Novel medical education stresses on enabling self-directory learning and increasing learning hours outside the classrooms. Accordingly, we hypothesize that innovations in educational technology can enhance the learning outcomes of ORL-HNS. This study is aimed to determine whether mobile technology in e-learning (M-TEL) is an effective tool for the instruction of ORL-HNS and to compare effects of different cognitive styles on learning outcomes of M-TEL with various modules of medical education. This is a randomized controlled trial. We will recruit 60 UME students without previous training in ORL-HNS to undergo the Group Embedded Figures Test to determine their cognitive styles such as field dependence or field-independence. After blinded randomization, students are instructed on two modules of emergent ORL-HNS disorders, using either a standard e-learning of text-figure Power Point show or an interactive multimedia module. Subjects are evaluated on emergent ORL-HNS disorders using text-based assessment and multimedia assessment take place prior to and following instruction. After 7 days later, they will be assessed using global satisfaction score and AttrakDiff2 questionnaire. We anticipate that this study can confirm M-TEL can enhance the efficiency of the instruction of ORL-HNS and understand differences in learning outcomes of M-TEL with various modules of medical education between field dependence and filed independence using this platform.
Background: New designs of 6-year undergraduate medical education (UME) mainly include (1) integral curricula of body organ system, (2) multiple methods of clinical teaching and assessment, and (3) generalism in UME. UME is meant to enable graduates to become undifferentiated general physicians. Accompany with decreasing educational hours in the classrooms and hospital, essential but minor components of primary healthcare such as ophthalmology and otolaryngology-head and neck surgery (ORL-HNS) is disproportionately under-represented in UME. In Canada, substantial downstream effects on managing ORL-HNS problems have been noted in family medicine residents. In order to improve learning insufficiency and enhance clinical competency without increasing extra-hours in the classrooms and hospitals, novel medical education stresses on enabling self-directory learning and increasing learning hours outside the classrooms. Accordingly, we hypothesize that innovations in educational technology can enhance the learning outcomes of ORL-HNS. Purposes: This study is aimed to determine whether mobile technology in e-learning (M-TEL) is an effective tool for the instruction of ORL-HNS and to compare effects of different cognitive styles on learning outcomes of M-TEL with various modules of medical education. Material and Methods: This is a randomized controlled trial. Firstly, we have been setup a e-learning platform of the Top 10 emergent ORL-HNS disorders with translating into an application (APP) function that can execute in mobile devices. Secondly, we will recruit 60 UME students without previous training in ORL-HNS to undergo the Group Embedded Figures Test to determine their cognitive styles such as field dependence or field-independence. After blinded randomization, students are instructed on two modules of emergent ORL-HNS disorders, using either a standard e-learning of text-figure Power Point show or an interactive multimedia module. Subjects are evaluated on emergent ORL-HNS disorders using a text-based assessment and a multimedia assessment take place prior to and following instruction. Anticipating Outcome: This study can (1) establish a M-TEL of ORL-HNS that can deliver an innovatively mobile e-learning to supplement the deficiency of the classroom hours, (2) confirm M-TEL can enhance the efficiency of the instruction of ORL-HNS, and (3) understand differences in learning outcomes of M-TEL with various modules of medical education between field dependence and filed independence using this platform.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
OTHER
Masking
NONE
Enrollment
60
UME students learn the Top 10 emergent ORL-HNS disorders using the M-TEL including the IM module or the PPS module.
Percentage Change in Multiple-choice Question (MCQ) Scores
Subjects will undergo the duplicated 15-minute MCQ tests before after the M-TEL Subjects will undergo the duplicated 15-minute MCQ tests 15 minutes before the M-TEL intervention with either the IM module or the PPS module and immediately after the M-TEL intervention.
Time frame: before and immediately after the M-TEL intervention
Percentage Change in Multimedia Situation Test (MST) Scores
Subjects will undergo the duplicated 15-minute MST tests 15 minutes before the M-TEL intervention with either the IM module or the PPS module and immediately after the M-TEL intervention.
Time frame: before and immediately after the M-TEL intervention
Global Satisfaction Score
Global satisfaction score is measured using a visual analogue scale from 0 (very dissatisfied) to 10 (very satisfied) after 7 days post M-TEL.
Time frame: 7 days after the M-TEL intervention
AttrakDiff2 Questionnaire: Pragmatic Quality Score
For more delicately evaluate the acceptance of technical innovations, we will assess "user experience" using the AttrakDiff2. AttrakDiff2 is developed as a tool by Hassenzahl's research group to be able to quantify attractive, identifiable, stimulating, and pragmatic qualities. The tool consists of 28 seven-step items whose poles are opposite adjectives (e.g. "confusing - clear", "unusual - ordinary", "good - bad"). Each set of adjective items is ordered into a scale of intensity. Each of the mean values of an item group creates a scale value for pragmatic quality (PQ), hedonic stimulation (HQ-S), hedonic identification (HQ-I), and attractiveness (ATT) (range: -3-3).
Time frame: 7 days after the M-TEL intervention
AttrakDiff2 Questionnaire: Hedonic Stimulation
For more delicately evaluate the acceptance of technical innovations, we will assess "user experience" using the AttrakDiff2. AttrakDiff2 is developed as a tool by Hassenzahl's research group to be able to quantify attractive, identifiable, stimulating, and pragmatic qualities. The tool consists of 28 seven-step items whose poles are opposite adjectives (e.g. "confusing - clear", "unusual - ordinary", "good - bad"). Each set of adjective items is ordered into a scale of intensity. Each of the mean values of an item group creates a scale value for pragmatic quality (PQ), hedonic stimulation (HQ-S), hedonic identification (HQ-I), and attractiveness (ATT) (range: -3-3).
Time frame: 7 days after the M-TEL intervention
AttrakDiff2 Questionnaire: Hedonic Identification
For more delicately evaluate the acceptance of technical innovations, we will assess "user experience" using the AttrakDiff2. AttrakDiff2 is developed as a tool by Hassenzahl's research group to be able to quantify attractive, identifiable, stimulating, and pragmatic qualities. The tool consists of 28 seven-step items whose poles are opposite adjectives (e.g. "confusing - clear", "unusual - ordinary", "good - bad"). Each set of adjective items is ordered into a scale of intensity. Each of the mean values of an item group creates a scale value for pragmatic quality (PQ), hedonic stimulation (HQ-S), hedonic identification (HQ-I), and attractiveness (ATT) (range: -3-3).
Time frame: 7 days after the M-TEL intervention
AttrakDiff2 Questionnaire: Attractiveness
For more delicately evaluate the acceptance of technical innovations, we will assess "user experience" using the AttrakDiff2. AttrakDiff2 is developed as a tool by Hassenzahl's research group to be able to quantify attractive, identifiable, stimulating, and pragmatic qualities. The tool consists of 28 seven-step items whose poles are opposite adjectives (e.g. "confusing - clear", "unusual - ordinary", "good - bad"). Each set of adjective items is ordered into a scale of intensity. Each of the mean values of an item group creates a scale value for pragmatic quality (PQ), hedonic stimulation (HQ-S), hedonic identification (HQ-I), and attractiveness (ATT) (range: -3-3).
Time frame: 7 days after the M-TEL intervention
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