Effects of Differentiated Instruction and Gamification on Iranian EFL Learners’ Willingness to Communicate, and Speaking Motivation

Hamed Taghizadeh ¹ ( Department of English, Tabriz Branch, Islamic Azad University, Tabriz, Iran )
Mahnaz Saeidi ² ( Department of English, Tabriz Branch, Islamic Azad University, Tabriz, Iran )
Saeideh Ahanghari ³ ( Department of English, Tabriz Branch, Islamic Azad University, Tabriz, Iran )

Submited date : 2025-03-15 Accepted date : 2025-04-23

Keywords: Willingness to Communicate, Speaking Motivation, Differentiated Instruction, Gamification, Iranian EFL Learners,

Abstract :

 

The ability to communicate effectively in English is crucial for Iranian EFL learners, yet many struggle with low Willingness to Communicate (WTC) and speaking motivation due to anxiety, lack of practice, and rigid teaching methods. This study explores the impact of Differentiated Instruction (DI) and Gamification (G) on improving WTC and speaking motivation among Iranian EFL learners. A quasi-experimental design was employed with 108 B2-level learners at Safir Language Institute in Iran, divided into three groups: one receiving DI, another experiencing G-based instruction, and a control group following conventional teaching. Participants were assessed using validated WTC and speaking motivation scales before and after a 10-week intervention. Statistical analyses, including ANOVA and t-tests, revealed significant improvements in both WTC and motivation in the experimental groups, with Gamification showing the highest gains. Qualitative findings from semi-structured interviews indicated that learners in both DI and G groups reported increased confidence, engagement, and a more positive attitude toward speaking. The study concludes that interactive, learner-centered strategies like DI and Gamification can effectively address communication barriers in Iranian EFL classrooms. These findings have implications for EFL pedagogy, suggesting a shift toward more engaging and personalized teaching approaches.

The study concludes that interactive, learner-centered strategies like DI and Gamification can effectively address communication barriers in Iranian EFL classrooms. These findings have implications for EFL pedagogy, suggesting a shift toward more engaging and personalized teaching approaches.

 

 

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Full-Text:



Effects of Differentiated Instruction and Gamification on Iranian EFL Learners’ Willingness to Communicate, and Speaking Motivation

 

1Hamed Taghizadeh, Ph.D. Candidate, Department of English, Tabriz Branch. Islamic Azad University, Tabriz, Iran

[e-mail]

*2Mahnaz Saeidi, Professor, Department of English, Tabriz Branch. Islamic Azad University, Tabriz, Iran

[e-mail]

3Saeideh Ahangari, Associate Professor, Department of English, Tabriz Branch. Islamic Azad University, Tabriz, Iran

[e-mail]

2025/03/15 2025/04/23

        

Abstract

The ability to communicate effectively in English is crucial for Iranian EFL learners, yet many struggle with low Willingness to Communicate (WTC) and speaking motivation due to anxiety, lack of practice, and rigid teaching methods. This study explores the impact of Differentiated Instruction (DI) and Gamification (G) on improving WTC and speaking motivation among Iranian EFL learners. A quasi-experimental design was employed with 108 B2-level learners at Safir Language Institute in Iran, divided into three groups: one receiving DI, another experiencing G-based instruction, and a control group following conventional teaching. Participants were assessed using validated WTC and speaking motivation scales before and after a 10-week intervention. Statistical analyses, including ANOVA and t-tests, revealed significant improvements in both WTC and motivation in the experimental groups, with Gamification showing the highest gains. Qualitative findings from semi-structured interviews indicated that learners in both DI and G groups reported increased confidence, engagement, and a more positive attitude toward speaking. The study concludes that interactive, learner-centered strategies like DI and Gamification can effectively address communication barriers in Iranian EFL classrooms. These findings have implications for EFL pedagogy, suggesting a shift toward more engaging and personalized teaching approaches.

Keywords: Willingness to Communicate, Speaking Motivation, Differentiated Instruction, Gamification, Iranian EFL Learners

INTRODUCTION

English serves as a vital bridge to global opportunities, making its mastery a priority for Iranian learners of English as a Foreign Language (EFL). Among the language skills, speaking stands out as essential for effective interaction, yet it poses unique challenges in Iran (Richards, 2015). Many learners hesitate to engage in oral communication, constrained by anxiety, limited practice opportunities, and a classroom culture rooted in traditional, teacher-led methods (Pattapong, 2015; Khajavy et al., 2018). This reluctance not only stifles their ability to express ideas but also dampens their enthusiasm for learning to speak (Farhady & Tavassoli, 2020).

To tackle these barriers, this study investigates two progressive teaching strategies i.e. differentiated Instruction (DI) and gamification (G). DI customizes learning experiences to reflect students’ individual strengths, preferences, and readiness (Tomlinson, 2017), while gamification introduces game-inspired features to spark engagement (Deterding et al., 2019). Both approaches hold potential to boost Iranian EFL learners’ Willingness to Communicate (WTC)—their readiness to initiate or join conversations in English—and their Speaking Motivation, the drive to improve oral skills. Despite growing interest in these methods, their specific effects on WTC and motivation in the Iranian context remain underexplored. This article examines how DI and gamification can inspire Iranian learners to embrace speaking with confidence and enthusiasm. Understanding the influence of DI and gamification begins with defining WTC and Speaking Motivation, alongside the frameworks supporting these instructional approaches.

Willingness to Communicate (WTC)

Willingness to Communicate (WTC) refers to a learner’s inclination to engage in L2 communication when opportunities arise (MacIntyre et al., 2019). It blends psychological readiness, social context, and linguistic confidence, shaped by factors like self-assurance, anxiety levels, and motivation (Peng, 2019). In EFL settings, WTC is a pivotal predictor of oral proficiency, as learners who actively participate gain more practice and refine their skills (Yashima et al., 2018). For Iranian EFL learners, WTC is often low due to cultural norms favoring reticence and fear of errors (Khajavy et al., 2018). Classroom environments that emphasize rote learning over interaction further suppress their desire to speak (Farhady & Tavassoli, 2020). Enhancing WTC could thus unlock greater communicative competence, making it a key focus of this study.

Speaking Motivation

Speaking Motivation encompasses the internal and external forces propelling learners to develop their oral abilities (Dörnyei & Ushioda, 2021). Drawing from Self-Determination Theory, it includes intrinsic motivation (personal satisfaction from speaking) and extrinsic motivation (external rewards like grades) (Ryan & Deci, 2020). Motivated learners invest more effort, persist through challenges, and achieve better rresults (Guilloteaux & Dörnyei, 2018). In Iran, speaking motivation often wanes due to uninspiring lessons and limited real-world application (Namaziandost et al., 2021). Fostering this drive is crucial, as it directly influences learners’ willingness to engage orally and their long-term success in English.

Differentiated Instruction (DI)

Differentiated Instruction (DI) adapts teaching to learners’ diverse needs, offering personalized pathways to growth (Tomlinson, 2017). By adjusting content, activities, and feedback based on readiness and interests, DI creates a supportive setting for skill development (Santangelo & Tomlinson, 2021). In EFL classrooms, it addresses varied proficiency levels, enhancing participation (Valiandes & Neophytou, 2018). For WTC and motivation, DI can build confidence by matching tasks to learners’ abilities, reducing anxiety and encouraging communication (Tomlinson, 2017). In Iran, where standardized teaching often discourages individual expression (Namaziandost et al., 2020), DI could ignite learners’ enthusiasm for speaking.

Gamification (G)

Gamification enhances learning by weaving in game-like elements such as rewards and challenges (Deterding et al., 2019). Using platforms like ClassCraft, it motivates learners through interactive, enjoyable experiences (Sailer & Homner, 2020). Rather than creating full games, gamification enriches existing tasks, making them more appealing (Kapp et al., 2019). For speaking, gamification can lower inhibitions and boost motivation by rewarding participation, fostering WTC (Wang & Tahir, 2020). In the Iranian context, where disengagement is common (Namaziandost et al., 2021), this approach could transform speaking into a rewarding endeavor.

Objectives of the Study

The primary goal of this study is to investigate how Differentiated Instruction (DI) and Gamification (G) influence Iranian EFL learners' willingness and motivation to speak English. The specific objectives include:

--To examine the effectiveness of Differentiated Instruction (DI) in improving Iranian EFL learners' Willingness to Communicate (WTC).

--To investigate the impact of Gamification (G) on Iranian EFL learners' Willingness to Communicate (WTC).

--To analyze how Differentiated Instruction (DI) influences Speaking Motivation among Iranian EFL learners.

--To assess the effectiveness of Gamification (G) in enhancing Speaking Motivation among Iranian EFL learners.

--To compare the relative effectiveness of DI and G in fostering WTC and Speaking Motivation.

--To explore learners’ perceptions of DI and Gamification as tools for improving speaking confidence and motivation.

--To identify the key motivational and psychological factors that contribute to increased engagement and communication in DI and G-based instruction.

Research Questions

This study sought to investigate the impact of Differentiated Instruction (DI) and Gamification (G) on Iranian EFL learners' Willingness to Communicate (WTC) and Speaking Motivation. The following research questions guided the study:

RQ1. What is the effect of Differentiated Instruction (DI) on Iranian EFL learners’ Willingness to Communicate (WTC) and Speaking Motivation?

RQ2. What is the effect of Gamification (G) on Iranian EFL learners’ Willingness to Communicate (WTC) and Speaking Motivation?

RQ3. How do the effects of Differentiated Instruction (DI) and Gamification (G) compare in improving WTC and Speaking Motivation?

RQ4. To what extent do Iranian EFL learners perceive DI and Gamification as effective methods for enhancing their willingness to speak English?

RQ5. What are the underlying factors contributing to learners’ engagement and motivation when exposed to DI and G-based instruction?

Research Hypotheses

Based on the research questions and existing literature, the study tested the following hypotheses:

H1: Differentiated Instruction (DI) significantly enhances Iranian EFL learners’ Willingness to Communicate (WTC) compared to traditional instruction.

H2: Gamification (G) significantly enhances Iranian EFL learners’ Willingness to Communicate (WTC) compared to traditional instruction.

H3: Differentiated Instruction (DI) significantly enhances Iranian EFL learners’ Speaking Motivation compared to traditional instruction.

H4: Gamification (G) significantly enhances Iranian EFL learners’ Speaking Motivation compared to traditional instruction.

H5: Gamification (G) has a greater impact on WTC and Speaking Motivation compared to Differentiated Instruction (DI).

H6: Iranian EFL learners perceive Gamification (G) as a more engaging and effective approach for enhancing oral communication skills than Differentiated Instruction (DI).

 

LITERATURE REVIEW

 

Recent research sheds light on DI and gamification’s potential to enhance WTC and speaking motivation, though their application in Iranian EFL settings merits further exploration. Studies on WTC emphasize its role in language learning. Peng (2019) found that supportive classroom dynamics increase WTC, reducing anxiety and boosting participation. Yashima et al. (2018) linked higher WTC to frequent communication practice, suggesting that engaging strategies could amplify this effect. For Iranian learners, cultural and psychological barriers often suppress WTC (Khajavy et al., 2018), highlighting the need for innovative interventions. Speaking motivation research underscores its impact on effort and achievement. Guilloteaux and Dörnyei (2018) showed that motivated learners exhibit greater persistence in oral tasks, while Dörnyei and Ushioda (2021) noted that interactive methods sustain motivation over time. In Iran, low motivation stems from monotonous instruction (Farhady & Tavassoli, 2020), pointing to a gap these strategies could fill. DI studies highlight its motivational benefits. Namaziandost et al. (2020) reported that DI increased Iranian learners’ engagement in vocabulary tasks, suggesting it could similarly inspire speaking. Sapan and Mede (2024) found DI enhanced Turkish EFL students’ motivation and autonomy, indicating its potential to foster WTC in similar contexts. By personalizing learning, DI could counter Iran’s uniform teaching traditions (Namaziandost et al., 2020).

Gamification research focuses on engagement. Wang and Tahir (2020) observed that gamified tasks heightened participation in EFL settings, though long-term motivation varied. Krystalli and Arvanitis (2024) noted gamification’s success in boosting communicative willingness, particularly when aligned with clear goals. For Iranian learners, gamification could address disinterest and anxiety (Namaziandost et al., 2021), yet its specific impact on WTC and motivation remains understudied. The literature reveals a gap: comparative analyses of DI and gamification’s effects on WTC and speaking motivation among Iranian EFL learners are scarce. Given the local challenges of reticence and disengagement (Khajavy et al., 2018), this study offers a timely investigation.

 

METHOD

 

This study adopted a quasi-experimental design to explore the effects of Differentiated Instruction (DI) and Gamification (G) on Iranian EFL learners’ Willingness to Communicate (WTC) and Speaking Motivation. Conducted at Safir Language Institute in Bandar Abbas, Iran, the research compared two experimental groups—one receiving DI and the other G—against a control group, using pre- and post-intervention assessments to measure rresults over a 10-week period.

Participants

Participants were 108 B2-level EFL learners (aged 16–21) selected from a pool of approximately 400 students across six intact classes at Safir Language Institute via convenience sampling, reflecting naturalistic classroom settings. The Oxford Quick Placement Test (OQPT; Cronbach’s α = .91), a 60-item measure of listening, reading, and grammar skills (Geranpayeh, 2003), was administered in a 45-minute session to ensure proficiency homogeneity. Learners scoring 40–47 (CEFR B2) were included, excluding 12 outliers, and randomly assigned using a number generator into three groups: DI (n=36), G (n=38), and control (n=34), with an approximate gender balance (close to 50% male/female) verified post-assignment.

Instruments

WTC was assessed using an adapted Willingness to Communicate questionnaire (MacIntyre et al., 2001; Cronbach’s α = .85), a 28-item 5-point Likert-scale tool (1 = strongly disagree, 5 = strongly agree) measuring readiness across contexts (e.g., “I am willing to speak English in a group”), piloted with 10 Safir learners (α = .84). Speaking Motivation was evaluated with the Speaking Motivation Scale (SMS; Yeşilyurt, 2008; Cronbach’s α = .89), a 31-item Likert-scale instrument capturing intrinsic (e.g., “Speaking English excites me”) and extrinsic (e.g., “I speak English for good grades”) dimensions, validated in a pilot with 10 learners (α = .87). Semi-structured interviews, developed by a panel of three experts and piloted with five B2 learners, featured 15 open-ended questions (e.g., “How did [DI/G] affect your desire to speak English?”) to probe perceptions, conducted in Persian and translated to English.

Procedure

The study spanned 20 sessions over 10 weeks (two 90-minute sessions weekly). In Week 1, after obtaining informed consent in English and Persian (with parental consent for minors per APA, 2017), the OQPT (Session 1) and pre-intervention SMS and WTC assessments (Session 2, 20 and 15 minutes respectively) established baselines. The 18-session treatment (Sessions 3–20) involved: the DI group engaging in customized speaking activities—adjusted for proficiency and preferences (e.g., tiered tasks, peer collaboration)—to build confidence (Tomlinson, 2017); the G group using ClassCraft, earning rewards for oral participation (e.g., points for dialogues) to enhance engagement (Deterding et al., 2019); and the control group receiving traditional instruction with teacher-led questions. Instructors, trained in a two-day workshop, ensured fidelity via weekly researcher reviews. Post-intervention (Session 20), all participants completed the SMS and WTC measures, with 20 participants (10 DI, 10 G) purposively selected for interviews based on diverse pre-test profiles.

Data Analysis Procedure

Quantitative data from the SMS and WTC questionnaire were analyzed in SPSS v.26. Shapiro-Wilk tests confirmed normality (p > .05), followed by one-way ANOVAs comparing post-test means across groups, with Tukey post-hoc tests for significant differences (p < .05), and paired t-tests assessing within-group changes. Qualitative interview data were transcribed, coded in MAXQDA v.2020 using Interpretive Phenomenological Analysis (IPA; Smith et al., 2009), and themed (e.g., “WTC Enhancement”), with an inter-coder agreement of 88%, integrating quantitative and qualitative insights (Dornyei, 2007).

 

RESULTS

 

This section presents the rresults of the study, detailing the effects of the instructional strategies on the measured variables across the three groups, based on quantitative statistical analyses and qualitative interview insights.

Quantitative Results

In the following, the statistical findings from the study, analyzing the impact of the instructional approaches on the dependent variables across the groups using descriptive statistics, ANOVA, paired t-tests, and post-hoc tests to determine the significance and extent of observed differences are reported.

Table 1

The Mean Scores of Groups in Pretest

pretest
	N	Mean	Std. Deviation	Std. Error
Control	36	93.95	10.826	2.421
G	38	89.60	12.059	2.696
DI	34	85.40	9.327	2.086
Total	108	89.65	10.737	2.401

 

As presented in Table 1, the average scores for the Control, Gamification, and Differentiated Instruction groups are 93.95, 89.60, and 85.40, respectively, indicating that participants in the Control group demonstrate a greater willingness to communicate compared to the others. This variation in communication willingness could influence the data analysis process, necessitating further statistical evaluation. Consequently, the researcher employed an ANOVA test to determine if the observed performance differences were statistically significant. The rresults of this analysis are displayed in Table 2.

Table 2 

One-Way ANOVA for the Pretest

Sum of Squares		df	Mean Square	F	Sig.
Between Groups	731.100	2	365.550	.087	.061
Within Groups	6642.550	105	116.536
Total	7373.650	107

 

    The probability linked to the observed F-value (.061) exceeded the significance threshold of .05, leading to the conclusion that the three groups were part of the same population regarding their willingness to communicate prior to the intervention. Subsequently, following the treatment sessions, the participants’ willingness to communicate was reassessed to evaluate the effectiveness of the applied strategies. To investigate the influence of the teaching methods on the students’ willingness to communicate (WTC), a paired sample t-test was conducted. The pre-test and post-test results of the participants were analyzed using this paired sample t-test.

Table 3

Descriptive Statistics of Control Group

	N Statistic	Mean Statistic	Std. Error	Std. Deviation Statistic
Pre. Control	36	93.95	2.421	10.826
Post. Control	36	94.80	1.946	8.703
Pre. G	38	89.60	2.696	12.059
Post. G	38	100.95	2.333	10.435
Pre. DI	34	85.40	2.086	9.327
Post. DI	34	92.30	2.113	9.448

 

    As indicated in Table 3, the average scores of participants on both the post-test and pre-test of the WTC questionnaire across all groups have risen, suggesting an enhancement in their willingness to communicate (WTC). To assess whether this observed difference was statistically significant, the mean scores were evaluated using t-tests.

 

 

 

 

Table 4

Paired Samples t test of Control Group

		Paired Differences					t		df		Sig. (2-tailed)
		Mean	Std. Deviation	Std. Error Mean	95% Confidence Interval of the Difference
					Lower	Upper
Pair 1	Post. Control- Pre. Control	- .850	13.635	3.049	-5.532	7.232		.279		19		.783
Pair 2	Post. G Pre. G	- 11.350	12.119	2.710	5.678	17.022		4.188		19		.000
Pair 3	Post. DI Pre. DI	- 6.900	10.161	2.272	2.144	11.656		3.037		19		.007

 

Based on the data summarized in Table 4, it was determined that the probability linked to the t-observed value (.27) exceeded the significance threshold of .05, indicating that the conventional teaching method did not significantly impact the students’ willingness to communicate (WTC). In simpler terms, while the Control group’s post-test mean score was higher than their pre-test score, this difference lacked statistical significance. Conversely, the probability tied to the t-observed value (4.18) for the gamification technique was below the .05 significance level, demonstrating that gamification significantly influenced the students’ WTC.

Additionally, a separate paired sample t-test was conducted to evaluate the effect of Differentiated Instruction (DI) on enhancing EFL learners’ willingness to communicate. The results showed that DI significantly improved the students’ WTC, as the probability associated with the t-observed value (3.03) was less than the .05 significance level. Given that two of the teaching strategies proved effective in boosting participants’ willingness to communicate, and considering that all participants initially exhibited similar WTC levels in the first questionnaire administration, the researcher opted to perform an additional ANOVA test to compare the groups and identify which one performed best.

Table 5

One-way ANOVA for the Posttest

Sum of Squares		df	Mean Square	F	Sig.
Between Groups	792.633	2	396.317	4.341	.018
Within Groups	5204.350	105	91.304
Total	5996.983	107

 

    As shown in Table 5, the probability linked to the F-observed value (.018) was below the significance threshold of .05. This led to the conclusion that there exists a statistically significant difference in the willingness to communicate (WTC) among students taught with different instructional methods. To identify the top-performing group or groups, a post hoc test was conducted.

Table 6 

Post Hoc Test Comparing the Significance of the Observed Difference in Pairs

Tukey HSD
(I) grouping	(J) grouping	Mean Difference (I-J)	Std. Error	Sig.
G	Control	6.150	3.137	.021
	DI	8.650	3.218	.005
Control	G	-6.150	3.137	.021
	DI	2.510	3.137	.049
DI	G	-8.650	3.218	.005
	Control	-2.510	3.137	.049

According to the data presented in table 6, it was determined that a notable difference existed between the Gamification and Control group teaching methods in enhancing participants’ willingness to communicate (WTC). Additionally, a significant distinction was found between Gamification and Differentiated Instruction, as the significance value of .005 was below the established alpha level. When comparing the results of the Control and Differentiated Instruction groups, a significant difference was also observed. Overall, the findings indicated that Gamification activities were the most effective teaching approach for improving participants’ WTC.

Moving forward with the study’s data analysis, the scores of the other dependent variable, motivation, were evaluated and compared. Likewise, the participants’ initial motivation levels were assessed before the treatment was applied.

Table 7

Descriptive Statistics of the Data Obtained from the Motivation Pretest

Descriptive
Motivation pretest
	N	Mean	Std. Deviation	Std. Error	95% Confidence Interval for Mean
					Lower Bound	Upper Bound
DI	38	103.87	2.564	.535	102.76	104.98
G	34	103.56	3.053	.720	102.04	105.07
Control	36	103.24	2.606	.569	102.05	104.42
Total	108	104.07	2.803	.253	103.57	104.57

 

Table 7 presents the descriptive statistics for all groups, including the mean scores and standard deviations of the motivation pretest results for both the experimental and control groups. The pretest score analysis revealed slight variations in the mean scores across the groups; consequently, ANOVA tests were conducted to determine if these minor differences held statistical significance.

The results of the one-way ANOVA, performed on the pretest scores of the experimental and control groups to assess any statistically significant differences in motivation among the groups, are outlined in Table 8.

Table 8

Analysis of Variances of the Motivation Pretest Scores of Experimental and Control Groups

ANOVA
Motivation pretest
	Sum of Squares	Df	Mean Square	F	Sig.
Between Groups	365.377	2	73.075	2.944	.091
Within Groups	2904.542	105	24.825
Total	3269.919	107

 

Upon reviewing the obtained results, it is clear that the differences in the mean scores of the motivation pretests between the experimental and control groups were not statistically significant, as the p-value of .09 exceeds the chosen significance level of 0.05 for this study. This suggests that, at the pretest stage, the groups exhibited comparable levels of motivation.

Following the pretests, the experimental group participants received specific treatments, while those in the control group followed the standard classroom procedures outlined by the institute’s curriculum without any particular intervention. After the treatment period, posttests were administered to all group participants to assess their motivation levels.

Table 9

Descriptive Statistics of Participants’ Motivation Pretest and Posttest Scores

Paired Samples Statistics
		Mean	N	Std. Deviation	Std. Error Mean
Pair 1	DI-pretest	103.86	23	2.563	.534
	DI-posttest	150.23	23	3.019	.629
Pair 2	G-pretest	103.55	18	3.052	.719
	G-posttest	161.00	18	2.543	.599
Pair 3	Control-pretest	103.23	21	2.605	.568
	Control-posttest	133.52	21	2.421	.528

 

As indicated by the data in Table 9, a comparison of the mean scores revealed variations between the pre- and post-test results across all groups. To examine these differences statistically and determine whether the applied techniques influenced participants’ motivation, paired sample t-tests were conducted.

Table 10

Paired Samples T-Test Comparing the Mean Scores Obtained from Motivation Pretests and Posttests

 

Paired Samples Test
		Paired Differences					t	df	Sig. (2-tailed)
		Mean	Std. Deviation	Std. Error Mean	95% Confidence Interval of the Difference
					Lower	Upper
Pair 1	DI-pretest - DI-posttest	-46.3680	3.94277	.82212	-44.70498	-41.29502	-52.303	34	.000
Pair 2	G-pretest - G-posttest	-57.4444	2.83304	.66776	-51.85328	-49.03560	-75.543	38	.000
Pair 3	Control-pretest - Control-posttest	-30.2857	2.30527	.50305	-18.33506	-16.23637	-34.362	36	.000

 

Considering the data presented in Table 10, and given that the significance level exceeded .05, it was determined that the differences observed between the pretest and post-test mean scores were statistically significant. As a result, it was concluded that the gamification, differentiated instruction, and conventional teaching techniques were all effective in enhancing participants’ motivation. Subsequently, given the initial similarity of the participants in the pretests, an ANOVA test was employed to compare the post-test scores across the groups.

Table 11

Descriptive Statistics of the data obtained from the Motivation Posttest

Descriptive
Motivation posttest
	N	Mean	Std. Deviation	Std. Error	95% Confidence Interval for Mean
					Lower Bound	Upper Bound
DI	38	150.23	3.020	.630	145.56	148.18
G	34	161.00	2.544	.600	152.74	155.26
Control	36	133.52	2.421	.528	119.42	121.63
Total	108	140.57	14.095	1.271	137.53	142.56

 

As shown in Table 11, which provides the descriptive statistics for the motivation post-test scores of all groups, the mean scores and standard deviations of the experimental and control groups were compared. The descriptive analysis of the post-test scores indicated that the mean scores across the groups varied to some degree. Consistent with the approach used for the pretest, an ANOVA test was conducted on the data to determine whether these differences between the groups were statistically significant.

Table 12

Analysis of Variances of the Motivation Posttest Scores

ANOVA
Motivation posttest
	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	23370.722	2	4674.144	630.778	.000
Within Groups	866.985	105	7.410
Total	24237.707	107

 

The findings from the ANOVA analysis in Table 12 indicate that the differences in motivation test scores among the groups are statistically significant, as the p-value of .00 is below the predetermined alpha level of 0.05 used to assess differences in this study. This suggests that the groups differ in their post-test results. Given that the observed differences between the groups are statistically significant, further comparisons between the instructional groups were conducted to identify the specific differences.

Table 13

Pairwise Comparison of Motivation Posttest Scores

Multiple Comparisons
Dependent Variable: Motivation posttest
Tukey HSD
(I) grouping	(J) grouping	Mean Difference (I-J)	Std. Error	Sig.	95% Confidence Interval
					Lower Bound	Upper Bound
DI	G	-10.77*	.874	.000	-6.19	-4.65
DI	Control	16.71*	.743	.000	12.54	28.73
G	Control	27.48*	.734	.000	14.35	6.44

 

Based on the differences in motivation levels between the groups, and taking into account the p-values and mean differences, it was determined that the Gamification group exhibited greater improvement in motivation compared to both the Control and Differentiated Instruction groups. When comparing the Control and Differentiated Instruction groups, it was further established that the Differentiated Instruction technique significantly enhanced learner motivation more effectively than the conventional teaching method applied in the Control group. Consequently, it was concluded that Gamification outperformed the other approaches in boosting learners’ motivation levels.

Qualitative Results (New Subsection)

To complement the quantitative results, semi-structured interviews with 20 participants (10 from DI, 10 from G) were analyzed using Interpretive Phenomenological Analysis (IPA), yielding three key themes: Enhanced Confidence in Speaking, Increased Enjoyment and Engagement, and Perceived Relevance of Tasks. These insights illuminate how DI and G influenced learners’ WTC and motivation, reflecting their lived experiences.

Theme 1: Enhanced Confidence in Speaking

Participants in both groups frequently cited increased confidence as a driver of their WTC. A Gamification participant shared, “earning points for speaking made me less afraid of mistakes. It felt like a game, not a test, so I talked more.” Similarly, a DI learner noted, “the teacher gave me tasks I could actually do, not too hard or too easy, so I wasn’t shy to try speaking.” This aligns with the significant WTC gains in G and DI, suggesting that tailored challenges (DI) and low-stakes rewards (G) reduced anxiety, a known barrier in Iran (Khajavy et al., 2018).

Theme 2: Increased Enjoyment and Engagement

Enjoyment emerged as a strong motivator, particularly for the G group. One of the participants explained, “ClassCraft was fun—like playing with friends. I wanted to join every discussion to level up.” This mirrors Gamification’s top motivation post-test score, indicating that game-like elements transformed speaking into a rewarding experience. DI learners also reported engagement, though differently. As one of DI-Participants said, “I liked choosing topics I cared about, like sports. It made me want to talk more.” The DI group’s motivation increase supports this, showing that personal relevance sustained effort, though less intensely than G’s interactive appeal.

Theme 3: Perceived Relevance of Tasks

Learners connected motivation to tasks they found meaningful. A G participant remarked, “The dialogues we practiced felt real, like chatting with foreigners, and the rewards kept me going.” In contrast, DI-Participant appreciated customization: “We worked in pairs on things I’m good at, like describing pictures, so I felt it was worth speaking.” These perceptions underscore Gamification’s edge in making speaking immediately gratifying, while DI’s strength lay in aligning tasks with individual strengths, boosting WTC and motivation significantly over Control.

 

DISCUSSION

 

The results of this quasi-experimental study revealed that Differentiated Instruction (DI) and Gamification (G) significantly develop Iranian EFL learners’ Willingness to Communicate (WTC) and Speaking Motivation, surpassing the impact of conventional methods. These findings align impeccably with Second Language Acquisition (SLA) theories and provide a compelling rationale for addressing the persistent issues of communication reluctancy and disengagement in Iranian EFL classrooms through innovative, learner-centered strategies.

Willingness to Communicate (WTC)

The enhanced WTC observed in the experimental groups aligns with MacIntyre et al.’s (2019) WTC model, which posits that psychological readiness and reduced anxiety are critical drivers of L2 communication. Gamification’s success can be attributed to its creation of a low-stakes, game-like environment, where learners felt liberated from the fear of errors—a pervasive barrier in Iran (Khajavy et al., 2018). Qualitative insights reinforce this, highlighting how rewards shifted focus from judgment to participation. DI, meanwhile, fostered WTC by tailoring tasks to learners’ abilities, building confidence through achievable challenges.

Speaking Motivation

The development in speaking motivation reflects Self-Determination Theory (Ryan & Deci, 2020), which ties motivation to intrinsic satisfaction and extrinsic incentives. Gamification’s superiority likely stems from its ability to infuse speaking with immediate enjoyment and tangible rewards, transforming a daunting skill into a gratifying experience. Learners’ accounts of fun and engagement underscore this, suggesting that game mechanics tapped into both intrinsic and extrinsic drives more potently than other approaches. DI’s strength lies in fostering autonomy and competence through personalized tasks, aligning with the theory’s focus on internal motivation (Farhady & Tavassoli, 2020).

Comparative Effectiveness of DI and G

The superior performance of G and DI over conventional teaching aligns with Dörnyei and Ushioda’s (2021) emphasis on engagement as a catalyst for language learning rresults. Gamification’s immersive, reward-driven approach likely accelerated WTC and motivation by making speaking instantly appealing, a critical advantage in a context where disengagement is prevalent (Namaziandost et al., 2021). DI, with its focus on individualized support, provided a steady foundation for growth, nurturing confidence and effort through relevance rather than rapid excitement. Qualitative feedback highlights this contrast: G turned speaking into a playful challenge, while DI made it a manageable, meaningful endeavor. Together, they outstrip traditional methods by addressing both psychological barriers and motivational needs unique to Iranian learners.

 

CONCLUSION

This study investigated the effects of Differentiated Instruction and Gamification on Iranian EFL learners’ Willingness to Communicate and speaking motivation. The findings provide strong evidence that both strategies can significantly enhance students’ readiness and motivation to speak English, addressing longstanding challenges in the Iranian EFL context.

The quantitative results demonstrated that both DI and G significantly improved WTC and speaking motivation compared to traditional instruction, with Gamification yielding the highest gains. Learners in the G group showed the greatest improvement, likely due to the engaging nature of game-based elements that reduce anxiety and foster participation. DI was also effective, particularly in enhancing confidence through personalized learning experiences tailored to individual student needs. These findings align with previous research on the role of interactive and student-centered methodologies in language acquisition.

The qualitative findings further support these conclusions, revealing that learners in the experimental groups felt more confident, enjoyed their speaking practice, and found the learning process more meaningful. Participants in the Gamification group highlighted how rewards and challenges made speaking fun, while those in the DI group appreciated the tailored tasks that matched their proficiency levels. These insights reinforce the idea that effective teaching strategies should accommodate students' psychological and motivational needs.

Given the challenges Iranian EFL learners face in developing oral proficiency, this study underscores the need for more dynamic, engaging instructional approaches. The results advocate for a shift away from rigid, teacher-centered methods toward flexible, interactive techniques that promote learner autonomy and confidence. Future research should further explore how these strategies can be optimized across different learning environments and proficiency levels.

Pedagogical Implications

These findings underscore the value of integrating DI and G to transform EFL speaking instruction in Iran. Gamification’s ability to activate eagerness suggests it as a powerful tool for initial engagement, while DI’s structured personalization supports sustained development—combined, they could offer a balanced approach to overcoming anxiety and apathy. Educators in Iran’s teacher-centric classrooms might adopt these strategies to shift toward learner agency, leveraging G’s immediacy and DI’s depth.

Suggestions for Further Research

While this study provides valuable insights into the impact of Differentiated Instruction and Gamification on Iranian EFL learners, several avenues remain for further exploration:

--Longitudinal Studies on WTC and Motivation: Future research could investigate the long-term effects of DI and Gamification beyond a 10-week period. Examining how these strategies influence WTC and speaking motivation over months or years would provide a clearer picture of their sustainability.

--Hybrid Models Combining DI and Gamification: Given that both approaches showed positive results, further studies could explore hybrid instructional models that integrate the personalization of DI with the engagement of G. Comparing combined methodologies to standalone implementations could reveal whether a blended approach maximizes language learning outcomes.

--Cross-Cultural Comparisons: Since cultural factors influence WTC and motivation, it would be beneficial to conduct comparative studies between Iranian EFL learners and students in other cultural contexts. This could help determine whether DI and G are universally effective or if modifications are needed for different learner populations.

--Neuroscientific Approaches to Speaking Anxiety: Using neuroimaging techniques like fMRI or EEG, researchers could analyze the neurological effects of DI and Gamification on learners’ anxiety levels and confidence when speaking. This could provide deeper insights into how these strategies reduce communicative apprehension.

--Exploring Teacher Perceptions and Implementation Challenges: Future studies could examine how teachers perceive the practicality and effectiveness of DI and G in real classroom settings. Understanding teachers' perspectives and the challenges they face in implementing these strategies could inform better training programs and instructional designs.

--Gamification Mechanics and Their Differential Effects: Further research could break down which specific elements of Gamification—such as rewards, competition, or role-playing—have the most impact on WTC and motivation. This would help refine game-based learning approaches for maximum effectiveness.

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Biodata

Hamed Taghizadeh is a Ph.D. candidate of TEFL at Tabriz Azad University, Tabriz, Iran. He has been teaching most of the courses related to English teaching. His main areas of interest include discourse analysis, methods and techniques of language teaching, linguistics, materials design and syntax.

Email: [e-mail]

Mahnaz Saeidi, Professor of Applied Linguistics at Islamic Azad University, Tabriz Branch, Tabriz, Iran, is the editor-in-chief of the Journal of English Language Pedagogy and Practice and the dean of faculty of foreign languages. She was frequently awarded for being the best researcher and won the best translator prize in the fourth round of Scientific, Research, and Technology ceremony of Islamic Azad University, 2016. She has published many books and articles and presented papers at national and international conferences. Her research interests are teacher education, corrective feedback, and AI-enhanced language learning.

Email: [e-mail]

 

Saeideh Ahangari is an associate professor of English Language Teaching at Islamic Azad University, Tabriz Branch, Iran. She mainly teaches language testing, research methodology, and teaching language methodology at the graduate level and her main areas of interest include teacher education, cooperative learning, language testing, and research. She has published many papers in international and national academic journals and also presented in conferences.

Email: [e-mail]

 

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