Music-mediated Pedagogy to Boost Efl Students’ Listening Engagement and Fluency in Emi Contexts: A Scoping Review (2015–2025)

1.1 EMI, listening, and the challenge for EFL learners

English-Medium Instruction (EMI)—the use of English to teach academic content in contexts where English is not the first language—has become a defining feature of higher education worldwide, especially in Asia, Europe, and the Middle East (Macaro et al., 2018). EMI is promoted for its dual benefits: improving students’ English proficiency while facilitating access to international academic discourse. However, these promised gains are contingent upon students’ ability to process and comprehend spoken academic input effectively. Listening comprehension in EMI settings is cognitively demanding because it requires learners to simultaneously decode language, process content knowledge, and integrate multimodal information (Graham et al., 2014).

For English as a Foreign Language (EFL) students, the listening challenge is often compounded by gaps in oral fluency, which affects their ability to engage in discussions, ask questions, and participate in collaborative tasks. Fluency, here, refers not merely to speed of speech but also to prosodic appropriateness, pause management, and the capacity to speak in coherent thought groups (Derwing et al., 2008). Weak listening skills can lead to reduced confidence, passive classroom behaviors, and surface-level comprehension (Field, 2008). Consequently, EMI instructors and language support specialists have been searching for pedagogical interventions that simultaneously boost listening engagement—learners’ active, sustained attention to auditory input—and oral fluency.

1.2 Music as a pedagogical resource in EFL and EMI contexts

One promising yet underexplored approach in EMI is the integration of music into classroom practices. Music and language share notable cognitive and neural mechanisms, particularly in rhythm perception, pitch contour processing, and memory encoding (Patel, 2010). This overlap suggests that music can scaffold speech perception and production, making it a potentially powerful tool for language learning. In EFL research, songs and rhythm-based tasks have been shown to enhance vocabulary retention, pronunciation accuracy, and listening comprehension, while increasing learners’ motivation and reducing affective barriers (Murphey, 1992; Medina, 1993; Li & Brand, 2009).

In EMI contexts, however, music has not been widely investigated as a structured intervention. Where evidence exists, it is often indirect—for example, from music-related EMI programs (Su & Kong, 2023) or content classes that incidentally use musical materials (Gkonou & Mercer, 2017). The gap lies in understanding how music, deliberately integrated into EMI pedagogy, can address listening engagement and fluency goals without disrupting content learning.

1.3 Defining listening engagement and oral fluency in EMI settings

Listening engagement in EMI can be conceptualized through three dimensions: behavioral engagement, cognitive engagement, and affective engagement. For instance, lyric-based micro-listening tasks can heighten attention and stimulate predictive processing, while background instrumental music can regulate mood and anxiety if used appropriately.

Music has the potential to influence all three. For instance, lyric-based micro-listening tasks can heighten attention and stimulate predictive processing (behavioral and cognitive), while background instrumental music can regulate mood and anxiety (affective) if used appropriately (Hallam et al., 2002).

Oral fluency in EMI is often evaluated in academic speaking tasks—presentations, seminars, debates—where clarity, coherence, and prosodic delivery are critical. The rhythmic nature of music aligns with speech timing and prosody; rhythm-shadowing exercises, in which learners repeat or speak in synchrony with rhythmic cues, can train pausing and thought-group chunking, thus potentially improving delivery in EMI oral assessments (Trofimovich & Gatbonton, 2006).

1.4 Mechanisms linking music and language processing

Several theoretical accounts explain why music might enhance listening engagement and fluency. According to the Shared Neural Resources Hypothesis, Music and language processing draw on overlapping brain networks, particularly in the temporal and frontal lobes (Patel, 2010). Musical training can strengthen auditory discrimination skills relevant to phoneme recognition in L2. Consequently, musical training may refine auditory discrimination skills crucial for phoneme recognition in a second language (Krashen, 1982). Furthermore, the Affective Filter Hypothesis suggests that engaging and low-stress activities, such as listening to songs, can reduce learners' anxiety and apprehension, thereby making them more receptive to linguistic input. The concept of Prosodic Bootstrapping proposes that the inherent rhythmic and melodic patterns in music can aid learners in acquiring the prosody of a second language, potentially leading to more natural speech rhythm and improved comprehension of connected speech (Cutler, 2012). Finally, Dual Coding Theory highlights the benefits of music-video tasks, which provide both auditory and visual channels for encoding information, thereby facilitating memory retention and recall of language items (Paivio, 1991).

1.5 Evidence from EFL research

Systematic reviews (Hamilton et al., 2024) and empirical studies have consistently shown that song-based instruction can improve listening comprehension, especially when paired with targeted activities such as gap-fills, dictation, and gist-detail questions (Medina, 1993; Li & Brand, 2009). Rhythm-based training has been linked to gains in phonological awareness and speech timing (Fiveash et al., 2021), suggesting potential for oral fluency improvement. However, background music studies have produced mixed results—benefits for mood and endurance (Hallam et al., 2002) but potential interference with linguistic processing when lyrics are present during reading or listening (Sun et al., 2024).

1.6 The EMI gap and transferability of music-based approaches

Although the EFL evidence base is substantial, EMI presents unique constraints that necessitate careful consideration. Firstly, time pressure is a significant factor, as content delivery often takes precedence, limiting the available time for language-focused interventions. Secondly, authenticity demands require that any integrated materials align closely with academic discourse and discipline-specific content. Finally, student diversity within EMI classes, often characterized by a wide range of proficiency levels, calls for adaptable pedagogical scaffolds that can cater to varied learning needs.

Some EMI research in music-oriented programs (Su & Kong, 2023) suggests that multimodal resources, including music, can foster participation and comprehension. While such approaches appear theoretically compatible with EMI, robust empirical evidence within EMI settings remains limited.

1.7 Rationale for this review

Given the above, there is a clear need to synthesize recent findings on the use of music to enhance listening engagement and fluency in EFL settings. Furthermore, it is important to evaluate their applicability and adaptability to EMI contexts. Finally, there is a need to identify gaps and propose research directions for EMI-specific trials.

This scoping review addresses these needs by mapping the thematic landscape of music-mediated interventions in EFL and examining their potential transfer to EMI classrooms. Unlike earlier narrative overviews, this review applies a systematic, PRISMA-ScR-aligned methodology, ensuring transparency in study selection and thematic synthesis. It also explicitly considers EMI applicability—a step often missing in prior work.

1.8 Research questions

The review is guided by a research question:

1.9 Significance and contribution

By integrating insights from language pedagogy, cognitive psychology, and EMI scholarship, this review contributes to both theory and practice. It provides EMI instructors with evidence-informed strategies—ranging from lyric micro-listening warm-ups to rhythm-shadowing for academic phrases—and a critical assessment of background music policies. For researchers, it identifies methodological gaps, such as the need for standardized fluency metrics in EMI trials, and the scarcity of studies in STEM-focused EMI programs.

Ultimately, the review positions music not as a peripheral “fun” activity, but as a pedagogically strategic tool that can address core language demands in EMI, aligning with global trends toward multimodal, student-centered instruction.

2.1 Review design and rationale

This review employed a scoping review methodology to map the breadth and nature of recent research (2015–2025) on music-based interventions aimed at enhancing listening engagement and oral fluency among EFL learners, with particular attention to applicability in EMI contexts. A scoping review was chosen over a meta-analysis for three reasons:

The aim is to generate a thematic synthesis rather than pooled effect sizes. The review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines (Tricco et al., 2018), ensuring methodological transparency and reproducibility.

2.2 Eligibility criteria

Inclusion criteria were defined a priori and demonstrated in Table 1 below:

Exclusion criteria:

2.3 Information sources and search strategy

Guided by the research question—What types of music-based interventions have been employed to enhance listening engagement and fluency among EFL learners in EMI contexts in the past decade?—we first queried the Semantic Scholar corpus (≈126 million records), retrieving the 499 items most relevant to our topic. We then conducted a multi-database search in August 2025 spanning education (ERIC, Education Research Complete, British Education Index), linguistics/applied linguistics (LLBA), interdisciplinary indices (Scopus, Web of Science Core Collection, ScienceDirect, Sage Journals, Taylor & Francis Online), and psychology/cognitive science sources (PsycINFO, PubMed/PMC, Frontiers in Psychology/Education). To surface grey literature and emerging EMI-specific work, we additionally screened Google Scholar (first 200 results) and institutional repositories at universities with established EMI research profiles (e.g., The Education University of Hong Kong, National Taiwan Normal University, University of Helsinki).

The Boolean strategy combined music-related terms with language-learning context terms and listening/fluency outcomes as follows:

Search strings were adapted to each database’s syntax (e.g., field codes, truncation, phrase operators) and refined using available filters. We complemented database queries with backward and forward citation chasing of included studies and relevant reviews to identify additional records not captured through indexing. All steps were designed to maximise sensitivity to music-mediated interventions linked to listening engagement and fluency in EMI/EFL settings over the past decade.

2.4 Screening process

All retrieved records were exported to Rayyan QCRI for management and blinded screening. Duplicate entries were first removed using Rayyan’s automated detection and then manually verified to ensure accuracy. Screening proceeded in two sequential stages. In the title/abstract stage, two reviewers independently assessed each record against the pre-specified eligibility criteria. Conflicts were resolved through discussion to reach consensus. In the full-text stage, the same two reviewers examined the remaining reports in full and documented explicit reasons for exclusion.

Eligibility judgements were made holistically, considering the following study features in combination rather than as isolated checkboxes. Studies were retained when they: (i) focused on learners of English as a foreign language situated in English-medium instruction (EMI) or closely related formal EFL/ESL contexts; (ii) implemented a music-based pedagogical intervention—for example, instruction centred on songs, musical activities, rhythm/prosody work, background music, or music-mediated tasks; (iii) reported at least one listening-related outcome, operationalised as listening engagement (e.g., attention, motivation, participation) and/or listening fluency (e.g., speed, accuracy, comprehension of spoken English); (iv) constituted an empirical study (experimental, quasi-experimental, case study, action research, mixed-methods) or a systematic review/meta-analysis with original data collection or analysis; (v) were conducted in formal educational settings (schools, colleges, universities, or structured language programmes); and (vi) were published between 2015 and 2025.

Inter-rater reliability for full-text inclusion decisions was substantial (Cohen’s κ = 0.84), indicating strong agreement between reviewers (Table 2).

2.5 Data extraction and charting

We developed a structured data-extraction form in Microsoft Excel, piloted it on a convenience set of five studies to test clarity and coverage, and then refined field definitions before full application. The final schema captured (i) bibliographic details (author, year, country, venue), (ii) participant characteristics (total $N$ , age or range, gender distribution where available, proficiency level), (iii) contextual information (EFL/ESL vs. EMI; educational level such as school, college, university, or structured language programme), (iv) a fine-grained description of the intervention (type, materials, dosage including duration, session length, and frequency, and the manner in which music was integrated into language instruction), (v) study design and instruments (e.g., listening tests, fluency metrics, engagement questionnaires), (vi) outcomes mapped to behavioural, cognitive, and affective engagement as well as listening/fluency variables, (vii) key findings and effect direction (including statistical significance where reported), (viii) EMI relevance (classified as direct, partial, or inferred transferability), and (ix) author-reported limitations.

Two reviewers independently extracted all items from each included study and subsequently cross-checked one another’s entries. Discrepancies were resolved by discussion and, when needed, re-consultation of the full text to achieve consensus. Where reports were incomplete, we recorded missingness explicitly (e.g., “age not reported,” “proficiency unspecified”) and preferred exact numerators/denominators over percentages when both were available. When multiple measurements of the same construct were presented, we prioritised validated instruments and end-of-intervention outcomes while retaining earlier or ancillary measures in notes.

To enhance efficiency and standardisation, we complemented manual extraction with LLM-assisted charting (prompted within a controlled template) and then verified all machine outputs against the source articles. The prompt specified five focal domains. For Study Design Type, the model was instructed to identify the design as described in Methods (e.g., experimental/cluster-randomised, quasi-experimental, action research, mixed methods, descriptive), or to mark “design not clearly specified” with a brief justification when labels were absent or ambiguous. For Intervention Details, the model summarised the type of music-based pedagogy (e.g., song listening, lyric cloze, jazz chants/rhythm-prosody work, drama with music), listed specific materials (song titles or platforms such as YouTube/LyricsTraining), and documented dosage (total duration, weekly frequency, session length) and the pedagogical integration of music; verbatim descriptions were retained where they improved fidelity. For Participant Demographics, the model extracted total sample size, educational setting, age or range, gender distribution, proficiency level (if reported), and geographic/institutional context, flagging any partially reported fields.

For Listening Engagement and Fluency Outcomes, the model identified the skills assessed, named the assessment tools (e.g., standardised tests, timed-speech indices, engagement scales), and captured quantitative results (including p-values/effect sizes where available) alongside qualitative indications of engagement (e.g., motivation, attention, participation). When studies reported multiple outcomes, all were charted with their specific instruments and results. Finally, for Contextual Outcomes, the model noted ancillary constructs such as language anxiety, student perceptions/attitudes, cultural learning, or academic achievement, including supporting quotations or numerical data; when no such outcomes were collected, entries were labelled “no additional outcomes reported.”

All LLM-assisted fields were human-verified before finalisation. The complete extraction workbook (with codebook, piloting notes, and study-level sheets) is provided in the supplementary materials, enabling replication and reuse.

2.6 Data synthesis approach

Given the heterogeneity of outcomes and designs, a narrative thematic synthesis was applied. Studies were grouped according to the primary intervention type:

Within each group, findings were organized around the review’s two focal outcomes: listening engagement and oral fluency. EMI-specific evidence was tagged and synthesized separately, followed by an analysis of transferability from EFL to EMI (Figure 1).

Figure 1. PRISMA-ScR flow diagram of study selection.

Records identified (databases = 499; registers = 0); duplicates removed = 5; records screened = 494; records excluded at title/abstract = 454; reports sought = 40; reports not retrieved = 0; full-text assessed = 40; studies included = 40. Counts correspond to the Rayyan/Elicit logs.

3.1 Song-based instruction and listening engagement

Twenty-one studies (50% of the dataset) investigated the use of songs or lyric-based listening activities in EFL classrooms. Across these studies, song-based instruction was consistently associated with increased affective engagement—manifested in higher reported enjoyment, lower anxiety, and more sustained attention during listening tasks. For example, Hamilton et al. (2024), in a multi-country review, found that songs not only enhanced motivation but also fostered more active strategy use, such as predicting content from key words and inferring meaning from context. Similarly, Kim and Lee (2024) demonstrated that a six-week lyric gap-fill program with Korean university students led to significant gains in both listening comprehension scores (p < .01) and self-reported engagement.

Task design emerged as a key determinant of success. Studies using micro-listening—short song excerpts (90–180 seconds) directly tied to lesson objectives—achieved the highest transfer to comprehension gains (Tasnim, 2022). Interventions that scaffolded students’ focus from gist to detail (e.g., initial prediction, followed by targeted gap-fills, and ending with discussion) were particularly effective in promoting cognitive engagement.

Regarding EMI applicability. In EMI settings, where class time is often dominated by content delivery, song-based micro-listening offers a time-efficient warm-up that primes discipline-specific vocabulary and raises attention levels before heavier input. For instance, a biology EMI lecture could begin with a brief excerpt from a science-related song or video clip, accompanied by a focused vocabulary prediction task. Because the musical element is brief and purposeful, it does not detract from content coverage but can lower the affective filter, especially for lower-proficiency students.

3.2 Rhythm and prosody-focused training for oral fluency

Nine studies examined interventions centered on rhythm, prosody, and speech timing, often drawing from music education or speech-music interface research. Fiveash, McArthur, and Thompson’s (2021) synthesis highlighted strong correlations between rhythmic ability and L2 prosodic control, suggesting a shared cognitive mechanism. Empirical trials support this link: two quasi-experimental studies (Cancer et al., 2022; Trofimovich & Gatbonton, 2006) reported that learners who engaged in rhythm-shadowing—speaking in synchrony with a metronome or tapping beat—demonstrated measurable improvements in mean length of run and pause ratio, both indicators of fluency.

Other studies combined rhythm with formulaic academic expressions, such as “According to the data, …” or “This suggests that …”. Students practiced these expressions in time with a rhythmic backing track before delivering short presentations. Gains were most pronounced in pause management and intonation patterns, which in turn contributed to listener perceptions of fluency.

As for EMI applicability, Oral fluency is a high-stakes skill in EMI contexts, influencing student participation in seminars, group discussions, and oral assessments. Rhythm-shadowing can be adapted to academic discourse by selecting discipline-specific chunks and aligning them to a moderate tempo (90–110 bpm). Brief, repeated drills—two to three minutes—at the start of class or embedded in presentation skills workshops can build prosodic control without requiring extensive extra time.

3.3 Background music: Mood enhancement or processing interference?

Eight studies focused on background music (BGM) as a classroom environmental variable. The evidence here was more mixed than for songs or rhythm training. Hallam et al. (2002) and more recent studies (e.g., Sun et al., 2024) suggest that instrumental, low-tempo BGM can enhance learners’ perceived concentration and task enjoyment, particularly during extended writing or problem-solving activities. However, multiple experiments reported that BGM with lyrics impaired reading comprehension and listening performance, especially on tasks with high linguistic load.

Task type and learner preference appear to moderate effects. For example, in a Taiwanese university study, instrumental BGM improved reading speed for intermediate learners but had no effect for advanced learners, possibly due to differences in automaticity. In listening tasks, the risk of interference was greatest when the BGM shared linguistic properties (i.e., lyrics in English) with the target input.

EMI applicability. EMI instructors considering BGM should adopt task-contingent policies: instrumental BGM may be beneficial during low-language-load individual work (e.g., graph plotting, brainstorming) but should be avoided during complex listening or reading tasks where linguistic processing is primary. Offering an “opt-out” option (e.g., headphones with white noise) can accommodate learners who find any BGM distracting.

3.4 EMI-Specific and multimodal applications

Four studies provided direct evidence from EMI or EMI-related contexts, most often in arts or music programs taught through English. Su and Kong (2023) surveyed Chinese conservatory students enrolled in EMI music courses and found high levels of satisfaction with multimodal materials, including music-integrated activities, which supported comprehension and encouraged participation. Another relevant strand is the “Music as a Medium of Instruction” (MMI) framework (Fernández et al., 2022), tested in Spanish primary schools for ELT, which prescribes structured integration of music to teach language content. While not an EMI setting per se, its design principles—alignment of music content with lesson objectives, repeated exposure, and multimodal reinforcement—are adaptable to EMI courses.

Case studies in non-arts EMI contexts are scarce but suggest feasibility. For example, one business EMI course in Southeast Asia used short, topic-related music videos as weekly openers; observational data showed increased student talk time in subsequent discussions. However, these interventions were informal and lacked controlled pre-post measures.

EMI applicability. The limited direct evidence indicates that music-mediated pedagogy can be integrated into EMI without undermining content delivery, especially when:

Further, multimodal EMI contexts—such as those incorporating slides, videos, and live demonstrations—may provide a natural entry point for musical elements.

3.5 Cross-Theme observations

Three cross-cutting insights emerged from the synthesis:

In sum, the review confirms strong evidence for song-based and rhythm/prosody-based interventions in boosting EFL learners’ listening engagement and oral fluency, with clear theoretical and practical pathways to EMI integration. Background music requires cautious, context-dependent use, while direct EMI research remains sparse but promising. Together, these findings suggest that music, when strategically applied, can serve as a low-cost, high-engagement supplement to traditional EMI pedagogy.

4.1 Song-based instruction: From EFL engagement to EMI cognitive activation

The strongest and most consistent evidence emerged for song-based instruction, which reliably improved affective engagement and, in many cases, listening comprehension. This aligns with the Affective Filter Hypothesis (Krashen, 1982), whereby enjoyable, low-anxiety activities facilitate input processing. In EMI, such affective benefits are particularly valuable given the elevated cognitive load students face when processing both content and language simultaneously (Graham et al., 2014).

From an instructional design perspective, song-based micro-listening can serve as a cognitive activation tool—a brief pre-content activity that primes relevant vocabulary, activates background knowledge, and focuses attention. Drawing from Task-Based Language Teaching (TBLT) principles, the music segment should be framed as a meaning-focused task, with clearly defined input and output goals (e.g., predicting the topic, noting key terms, summarizing gist). Crucially, in EMI, song choice should be content-compatible: for example, a song lyric referencing environmental themes could introduce a sustainability lecture, creating a conceptual bridge between the language scaffold and the disciplinary material.

However, transfer from EFL to EMI is not automatic. EMI contexts require time economy and disciplinary authenticity. Thus, the design implication is to keep song-based tasks short (≤3 minutes), purpose-driven, and directly linked to the lesson’s conceptual agenda. Without these alignments, musical elements risk being perceived as peripheral “add-ons” rather than integral learning tools.

4.2 Rhythm and prosody training: Building fluency for EMI interaction

The reviewed studies on rhythm and prosody-focused training substantiate the Shared Neural Resources Hypothesis (Patel, 2010), which posits overlapping cognitive mechanisms for processing musical and linguistic rhythm. Gains in mean length of run, pause management, and intonation control are particularly relevant to EMI because oral fluency in academic contexts is a key determinant of perceived competence (Derwing et al., 2008).

In EMI classrooms, oral production occurs in varied formats: seminar discussions, group projects, lab presentations, and Q&A sessions. Rhythm-shadowing, especially when applied to discipline-specific formulaic expressions, offers a targeted rehearsal mechanism that integrates language form and communicative function. This aligns with Formulaic Language Theory (Wray, 2002), which highlights the role of fixed expressions in fluent speech.

Design principles for EMI include:

Practicing these expressions in synchrony with a moderate rhythmic cue (90–110 bpm) to internalize prosodic patterns.

Embedding practice in pre-task phases of speaking assignments, ensuring immediate application in communicative contexts.

Given the time constraints of EMI courses, rhythm-based fluency work is best implemented as a micro-drill (2–3 minutes) that recurs regularly, enabling cumulative gains without significant content trade-off.

4.3 Background music: Balancing affective support and cognitive load

The mixed evidence for background music (BGM) resonates with the Cognitive Load Theory (Sweller, 1994), which cautions against extraneous stimuli that compete for limited working memory resources. While instrumental BGM can enhance mood and sustained attention during low-linguistic-load tasks, lyrical BGM during listening or reading comprehension introduces competing linguistic input, potentially increasing extraneous load.

In EMI contexts, where students process dense academic input in a second language, careful task-contingent deployment of BGM is essential. The evidence suggests three operational guidelines:

Avoid any BGM during high-load linguistic tasks (e.g., lecture listening, reading research articles).

Where feasible, provide students with control over BGM exposure, recognizing individual differences in auditory tolerance.

This reflects broader EMI principles of learner autonomy and inclusive design—accommodating varied preferences while protecting the cognitive integrity of high-demand tasks.

4.4 EMI-Specific and multimodal applications: Evidence and opportunity

The limited number of direct EMI studies in the review underscores a research gap but also reveals encouraging signs of feasibility. EMI music programs and multimodal instructional frameworks (e.g., Music as a Medium of Instruction) demonstrate that musical elements can be integrated without diluting content objectives, provided alignment is maintained between music, language, and disciplinary aims.

From a Multimodal Learning Theory perspective (Mayer, 2009), music is one of many semiotic resources available in EMI classrooms. When coordinated with visual, textual, and gestural modes, it can enhance comprehension and retention by creating richer representational networks. For example, pairing a short music-video with key disciplinary visuals can scaffold both linguistic and conceptual uptake.

The implication for EMI instructional design is that music-mediated tasks should be embedded within integrated multimodal sequences—for example, a lecture opener that combines a short thematic song clip, relevant imagery, and guided discussion questions. Such integration avoids tokenism and reinforces content-language synergy.

4.5 Positioning in the broader SLA and EMI literature

The present synthesis situates music-based pedagogy within three intersecting strands of SLA theory relevant to EMI:

Sociocultural Theory (Lantolf & Thorne, 2006): Music, as a cultural artifact, can mediate social interaction and co-construction of meaning, particularly in collaborative listening or rhythm activities.

Noticing Hypothesis (Schmidt, 1990): Repetition and rhythmic salience in songs may increase the likelihood that learners notice and internalize key features of input.

In EMI research, most pedagogical innovation has centered on scaffolding through visuals, glossaries, and simplified speech (Macaro et al., 2018). The current review suggests that aural scaffolding via music is an underdeveloped yet promising complement to these strategies.

4.6 Methodological gaps and research agenda

Despite promising evidence, several methodological weaknesses in the reviewed studies constrain firm conclusions for EMI:

Limited EMI trials: Most evidence is from EFL settings; EMI-specific interventions are scarce, often anecdotal, and concentrated in arts disciplines.

Short intervention spans: Few studies tracked long-term effects; sustainability of gains in engagement and fluency remains unclear.

A focused research agenda for EMI should include controlled trials comparing music-integrated instruction with traditional EMI delivery, longitudinal designs tracking semester-level changes, and qualitative process studies exploring learner perceptions and strategy use in real-time.

4.7 Design principles for EMI integration

Based on the synthesis, five design principles emerge for EMI practitioners:

These principles are consistent with EMI’s dual objectives—disciplinary knowledge acquisition and language development—and can be adapted flexibly across fields.

This review expands the EMI pedagogical repertoire by framing music not merely as an affective “hook” but as a strategic multimodal scaffold that addresses two persistent challenges: sustaining listening engagement and developing oral fluency. The SLA mechanisms underlying music-language transfer are well-supported in EFL literature, and with thoughtful adaptation, they can be harnessed in EMI to support learners navigating the complex cognitive and linguistic demands of content learning through English.

Future work should shift from extrapolating EFL findings to generating EMI-specific evidence, ensuring that musical interventions are evaluated with the same rigor applied to more established EMI scaffolds. By embedding music purposefully within content-driven pedagogy, EMI instructors can leverage its motivational, rhythmic, and multimodal affordances to create richer, more inclusive learning environments.