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Background: Although existing studies have shown that both repetitive transcranial magnetic stimulation (rTMS) and music therapy have advantages in the treatment of non‐fluent aphasia, the efficacy of the combination of these two methods remains to be investigated. Aims: To investigate the clinical efficacy of low‐frequency rTMS combined with music therapy on language function and depression in patients with non‐fluent aphasia after stroke. Methods & Procedures: A single‐blind parallel randomised controlled trial was conducted. Sixty patients (mean duration = 93.78 days) with non‐fluent aphasia after stroke were randomly divided into a traditional therapy group (n = 20), a music therapy group (n = 20) and a combined therapy group (n = 20, 1 Hz). The language function and depression were evaluated before and 3 weeks after treatment with the Chinese version of the Western Aphasia Battery scale, Boston Diagnostic Aphasia Examination scale and Stroke Aphasic Depression Questionnaire Hospital Version scale. Outcomes & Results: The combined therapy group was significantly better in all outcomes than the traditional therapy group and was significantly better in depression than the music therapy group. The music therapy group was significantly better in repetition and depression than the traditional therapy group. Language improvement was positively correlated with depression improvement. For adverse events, only two patients in the combined therapy group showed slight dizziness during rTMS treatment and their symptoms improved after rest. Conclusions & Implications: Our preliminary randomised controlled study indicates that low‐frequency rTMS combined with music therapy is feasible and safe in improving language function and depression in non‐fluent aphasia patients after stroke. WHAT THIS PAPER ADDS: What is already known on this subject: Repetitive transcranial magnetic stimulation (rTMS) and music therapy respectively have advantages in the treatment of non‐fluent aphasia after stroke, but whether the combination of the two methods is more effective is still unknown. What this paper adds to the existing knowledge: This is one of the first randomised control trials to investigate whether the clinical efficacy of low‐frequency rTMS combined music therapy for non‐fluent aphasia is better. The findings show that low‐frequency rTMS combined music therapy is superior to traditional therapy in spontaneous speech, auditory comprehension, repetition, naming, aphasia quotient, functional language level and depression, and superior to music therapy in depression, while music therapy is superior to traditional therapy in repetition and depression. What are the potential or actual clinical implications of this work?: Low‐frequency rTMS combined music therapy may be a better method for treatment of non‐fluent aphasia. [ABSTRACT FROM AUTHOR]

Background Study: The effects of the flipped classroom (FC) on students' academic performance remain ambiguous, and the use of pre‐class videos may be one of the main factors hindering students' progress. A software package called GeoGebra has been proposed as a substitute for pre‐class videos to aid students' learning. Objective: This study investigates the effect of the FC using GeoGebra (FCG) on mathematical performance and memory among senior secondary students. Methods: One hundred and sixty students of a senior high school in China were selected. A quasi‐experimental design was implemented in which the classes were split into the intervention group (FCG), control group A (FCV) and control group B (TL) by random assignment. Pretest, Post‐test 1 and Post‐test 2 were introduced. Results and Conclusion: The results indicate that both the FCG and the FC with pre‐class videos (FCV) were more effective than traditional lectures in enhancing students' academic test scores, and that the effect of the FCG was comparable to its video counterpart, F(2, 136) = 3.752, ρ = 0.026, η2 = 0.052. Although their effects were similar, the qualitative results revealed some hidden benefits associated with the replacement of pre‐class video with GeoGebra. Furthermore, although they were equally effective in promoting students' performance in the short‐term, the long‐term effects on academic performance of both forms of FC were non‐significant when compared with traditional lectures. Lay Description: What is already known about this topic: Flipped classroom is an effective strategy in teaching mathematics.Among those challenges, video may be one of the main factors hindering the effect of flipped classroom. What this paper adds: GeoGebra could be an effective alternative to video.Effect between the flipped classroom using GeoGebra and the flipped classroom using video were similar.Both the flipped classroom with GeoGebra and the flipped classroom with videos were more effective than traditional lectures. Implications for practice and/or policy: Students' short‐term performance could be enhanced by visualisation provided by flipped classroom.To enhance students' long‐term performance, an appropriate amount of homework is suggested. [ABSTRACT FROM AUTHOR]

Background: Video lectures which include the instructor's presence are becoming increasingly popular. Presenting a real human does, however, entail higher financial and time costs in making videos, and one innovative approach to reduce costs has been to generate a virtual speaking instructor. Objectives: The current study examined whether the use of a virtual instructor in video lectures would facilitate learning as well as a human instructor, and whether manipulating the virtual instructor's characteristics (i.e., voice and appearance) might optimize the effectiveness of the virtual instructor. Methods: Our study set four conditions. In the control condition, students watched a human instructor. In the experiment conditions, students watched one of (a) a virtual instructor which used the human instructor's voice and an AI image, (b) a virtual instructor which spoke in an AI voice with an AI image made to speak using text‐to‐speech and lip synthesis techniques, or (c) a virtual instructor with used an AI voice and an AI likable‐image of an instructor. Results and Conclusions: The AI likable instructor condition had a significant positive effect on students' learning performance and motivation, without decreasing the attention students paid to the learning materials. Implications: Our findings suggest that instructional video designers can make use of AI voices and AI images of likable humans as instructors to motivate students and enhance their learning performance. Lay Description: What is already known about this topic: Video lectures which include the instructor's presence are becoming increasingly popular.Presenting a virtual instructor (i.e., a pedagogical agent) in video lectures has been shown to reduce costs of video production, both financially and in terms of time. What this paper adds: An AI‐generated voice and an AI‐generated image facilitated more students' transfer performance than a human instructor.The AI likable instructor condition had a significant positive effect on students' learning performance and motivation, without decreasing the attention students paid to the learning materials. Implications for practice and/or policy: We encourage instructional designers to use AI‐generated voices and AI‐generated images connected to a virtual instructor instead of a human instructor in video lectures.We encourage instructional designers to use likable human images (as defined by the students themselves) as a way to motivate students more and enhance their learning performance. [ABSTRACT FROM AUTHOR]

In the increasing pervasiveness of today's digital society, mobile devices are changing the face of education. Students can interact with mobile devices in context‐aware environment. This paper presents a mobile application based on expert system (Plant‐E) for students to acquire knowledge about plant classification by answering decision‐making questions. In order to study effectiveness of Plant‐E and cognitive load of students who experience different kinds of interaction in learning process, another mobile application (Plant‐G) only providing information pages of plants was developed. A quasi‐experiment was conducted with three classes of 137 seventh graders. The three classes, Class A with 46 students using Plant‐E in campus, Class B with 44 students using Plant‐G in campus, and Class C with 47 students using Plant‐G in a traditional classroom, constitute three groups with different interaction complexity. The research conducted pretest, posttest, and delayed test to evaluate learning performance of students in three classes and used a questionnaire to investigate their perceptions and attitudes towards proposed system. Results show that interaction complexity has an impact on students' learning performance and mental effort in mobile learning; the higher the interaction complexity is, the higher mental effort and the better learning performance in mobile learning will be. Lay Description: What is already known about this topic: Mobile devices can be used to meet the urgency of learning need and can provide guidance and clues for learners in context‐aware environment.During mobile learning in context‐aware environment, students need to interact with mobile devices and environment.Mental effort reflects cognitive load related to interaction complexity, and it can affect learning performance.Self‐efficacy affects the degree of mental effort by affecting the firmness of performance goal.Cognitive load and learning performance are the main concerns that need to be considered when evaluating the effectiveness of mobile learning. What this paper adds: Interaction complexity has an impact on students' learning performance and mental effort in mobile learning.In terms of the three levels of interaction complexity in this study, the higher the interaction complexity is, the better the results that students will get in mobile learning.The higher the interaction complexity is, the higher the mental effort that students invested into in mobile learning would be.The medium self‐efficacy group invested the most mental effort and got the best grades, rather than the high or low group.Rule‐based mobile learning expert system is feasible and effective for students to learn by interacting with learning objects in context‐aware environment. Implications for practice and/or policy: Efforts should be made to make mobile learning systems more interactive; for example, learners can learn more effectively by interacting with mobile system, which can improve the frequency of observing learning objects.Rule‐based mobile learning expert system can give learners more opportunities to know how experts do when solving problems and can provide a potential method for students to learn in context‐aware environment. [ABSTRACT FROM AUTHOR]