The Predictive Role of Grammar Knowledge in Lower- and Higher-Order Thinking Skills within Vocational Education

doi:10.21203/rs.3.rs-7897515/v1

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Research Article

The Predictive Role of Grammar Knowledge in Lower- and Higher-Order Thinking Skills within Vocational Education

https://doi.org/10.21203/rs.3.rs-7897515/v1

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Linguistic proficiency contributes to the learners’ cognitive tasks in higher vocational education. This study examined the relationship between learners’ grammatical knowledge and their performance in lower- and higher-order thinking skills (LOTS) and (HOTS), in an English language lesson in higher vocational classrooms. A total of 134 students participated in the research, completing grammar-focused test items and cognitive assessments designed to measure basic comprehension and advanced analytical skills. The data were analysed using Pearson correlations in SPSS, confirmatory factor analyses and full measurement model within the structural equation modelling framework in Mplus. The measurement instruments exhibited strong reliability, achieving a Cronbach’s alpha of .839 for the 39 items. Confirmatory factor analysis further supported the validity of the three-factor structure, with all model fit indices indicating acceptable to good fit (χ²(699) = 812.51, p = .002, RMSEA = .035, CFI = .904, and TLI = .899), which means that the instruments consistently and accurately measured grammatical knowledge, LOTS and HOTS. The result revealed that grammar knowledge was not directly associated with learners’ LOTS or HOTS performance. However, it significantly predicted their lower- and higher-order thinking performance. A strong correlation was observed between LOTS and HOTS, and further analysis confirmed that grammar indirectly supports HOTS by first strengthening LOTS. Grammar provides a foundation for basic cognitive tasks, which subsequently enable more advanced reasoning. This suggests that grammar serves as an enabling tool rather than a direct driver of higher-order cognition.

grammatical knowledge

lower-order thinking skills

higher-order thinking skills

vocational education

Grammar instruction was regarded as the backbone of English language teaching, ensuring learners developed accurate structures (Wyatt & Dikilitaş, 2021). However, grammar is not just a set of rules (Davis, 2009), it is also a cognitive system that enables learners to process linguistic input, organise knowledge, and apply language in increasingly complex communicative situations (Wijnands et al., 2021). Therefore, knowledge of grammar is not only a linguistic resource but also a cognitive tool that shapes learners’ capacity to engage in various levels of thinking. A study by Donnelly et al. (2025) explored the strong relationship between grammar and early language development, and research by McCarthy et al. (2022) used grammar proficiency and feedback as a tool to assess writing skills. While they found that grammar comprehension provided minimal benefits to learners’ writing skills, they also demonstrated the positive impact of grammatical accuracy on academic writing proficiency. A review by Jago et al. (2025) examined the separate influence of grammar on later reading comprehension. They found a positive association between grammar comprehension and reading comprehension and word reading. Teachers and learners believe that grammar is important for developing speaking proficiency (Lakew et al., 2021). Grammar can help learners develop their oral language production skills. Additionally, a study by Ünaldı and Yüce (2021) investigated the potential links between foreign language grammar proficiency and critical thinking skills. The study examined 126 adult language learners in terms of their grammar proficiency and critical thinking skills. The researchers found that the participants’ grammar proficiency level scores correlated positively with critical thinking.

In educational psychology, the development of cognitive skills has been systematically conceptualised using frameworks such as Bloom’s Taxonomy and its subsequent revisions (Krathwohl, 2002). These models distinguish between lower-order thinking skills (LOTS), which include remembering, understanding, and applying knowledge, and higher-order thinking skills (HOTS), which involve analysing, evaluating, and creating. Within this framework, critical thinking and grammatical mastery are correlated (Youjun & Xiaomei, 2022).

Unlike traditional academic programmes, vocational institutions aim to produce graduates who can combine technical expertise with English language communicative competence (Teng, 2024). For example, tourism students must demonstrate grammatical accuracy when interacting with customers (Ho, 2020), while engineering students must be able to comprehend technical manuals and explain processes clearly (Nateghian, 2024). While both tasks require LOTS, professional environments also demand HOTS, such as solving problems in real situations within an English-language context (Su, 2025). Previous research by Chomphooyod et al. (2023) highlighted the development of grammar tasks in English learning with a high level of acceptance. However, the specific test levels were not explicitly identified. If grammatical knowledge plays a role in supporting these higher-order demands, then grammar-focused instruction may need to be reconceptualised as not merely a foundation for correctness, but also as a catalyst for critical thinking and professional reasoning (Robertson et al., 2018).

Despite these insights, several gaps remain. Previous investigations have rarely accounted for the broader cognitive processes supported by grammar. In particular, the distinction between LOTS and HOTS has not been systematically addressed in grammar research. Although Ünaldı and Yüce (2021) found a positive correlation between grammar proficiency and critical thinking, their research did not distinguish the respective contributions of grammatical knowledge to LOTS and HOTS. This leaves the question unanswered as to whether grammar primarily supports foundational tasks, higher-level reasoning, or both. Taken together, these gaps highlight the need for studies that investigate how grammar performance interacts with cognitive skill levels, rather than treating grammar as an isolated construct. Specifically, there is limited evidence on (1) the relationship between learners’ performance in grammar-focused tests and their performance in LOTS and HOTS tasks; and (2) the extent to which grammar predicts performance in different cognitive domains. The present study addresses these gaps and is guided by three research questions:

RQ(1) Are the used instruments valid to assess students’ grammatical knowledge, LOTS and HOTS?

RQ(2) How are learners’ performances on grammar-focused items directly related to their performance on tasks involving lower-order and higher-order thinking skills?

RQ(3) To what extent do grammar-focused items predict learners’ success in lower-order and higher-order thinking skills tasks? Can LOTS mediate this relationship?

Grammar Proficiency

Proficiency in grammar has contributed to the development of communicative skills (Sato & Oyanedel, 2019). From a structuralist perspective, grammar was initially conceptualised as a set of prescriptive rules that learners needed to master in order to construct grammatically correct sentences (Pawlak, 2020). However, grammar proficiency encompasses more than just the recognition and reproduction of grammatical structures; it also involves the skills to apply these structures flexibly in diverse contexts (Mirosław et al., 2023). Taken together, the theoretical framework of grammar proficiency positions grammar as a multifaceted construct encompassing rule knowledge, application, and adaptability in communication. It simultaneously functions as a linguistic foundation that ensures structural accuracy and as a pedagogical focus that informs instructional design and assessment. This framework establishes grammar not only as a fundamental component of language learning and a predictive factor for learners’ performance in broader educational contexts (Pawlak, 2013).

Lower-and Higher-Order Thinking

This research is based on the intersection of cognitive learning theory and linguistic competence frameworks. Together, these explain how grammar knowledge supports performance in cognitive tasks. According to Bloom’s taxonomy of educational objectives (Anderson & Krathwohl, 2001), cognitive tasks can be conceptualised as falling somewhere on a continuum ranging from LOTS, such as remembering (Sands et al., 2023), understanding and applying (Jansen & Möller, 2022), to HOTS, including complex thinking (Pacheco & Herrera, 2021; Ramírez-Montoya et al., 2022), critical thinking (Khalili et al., 2024; Koçoğlu & Kanadlı, 2025; Su, 2025), transferring knowledge to new situations (Newmann, 1990), and creation (Yeh, 2012). Grammar knowledge, processed as declarative knowledge, is more readily applied in tasks involving recognition (Alkhateeb & Albahr, 2025) and recall (Rong & Révész, 2025). However, transitioning to HOTS requires integration with metacognitive strategies (Wang et al., 2024), which extend beyond linguistic competence alone.

Research Design

This study employs a quantitative research methodology incorporating both correlational and predictive designs. The correlational design examines the relationships between grammar knowledge and learners’ performance on lower-order and higher-order cognitive tasks, while the predictive design assesses the extent to which grammar proficiency predicts success in these different cognitive domains. This approach enables the quantification of relationships between variables, providing robust evidence of the role of grammar in supporting cognitive performance. Adopting this focus enables the study to identify associations and evaluate the predictive contribution of grammar knowledge to students’ academic and cognitive outcomes in higher vocational education.

Participants

The participants were 134 students enrolled in higher vocational education programs in Indonesia. They represented a range of academic disciplines, including business, tourism, and information technology. This population was selected based on the relevance of vocational education, in which learners must balance technical knowledge with English communication skills. The sample size was deemed sufficient for correlational and regression analyses, providing adequate statistical power to detect significant relationships.

Procedures

Data collection took place in a classroom setting under standardised testing conditions. Students completed a grammar-focused test alongside a set of cognitive tasks, which were classified as LOTS and HOTS based on Bloom’s taxonomy. Test administration was overseen to ensure validity and minimise external influences. Once completed, the test results were coded numerically and prepared for statistical analysis. This procedure was designed to minimise bias and ensure uniformity across participants, enabling fair comparisons to be made and reliable inferences to be drawn from the dataset.

Tests Items and Reliability

This research used a grammar and cognitive comprehension test consisting of 50 multiple-choice items. Each item contained four possible answers, only one of which was correct. The test items were scored dichotomously, correct answers were awarded one point (1) and incorrect answers were given zero points (0). Lower-order thinking tasks reflected recall- and comprehension-based items, whereas higher-order tasks included application-, analysis-, and synthesis-based items. Scores for each domain were aggregated and analysed to provide meaningful measures of learners’ performance. In the current research context, the initial 50-item scale demonstrated inadequate internal consistency. To improve the scale's psychometric properties, a comprehensive item analysis was conducted. Items with low or negative correlations were deleted. Several items were found to correlate negatively with the total scale score, indicating they were measuring a construct contrary to the intended one. We examined whether the removal of each problematic item would increase the overall reliability of the scale. The test items representing grammar based on questions Q1, Q2, Q3, Q4, Q6, Q7, Q8, Q9, Q10, Q11, Q13, Q14, Q16, Q17, and Q18. The remaining 24 items were classified as LOTS and HOTS. The LOTS test items included Q32, Q39, Q40, Q41, Q43, Q44, Q45, Q47 and Q48. These measured remembering, understanding, and applying language knowledge. Furthermore, HOTS involved Q20, Q21, Q23, Q24, Q25, Q26, Q27, Q28, Q31, Q34, Q35, Q36, Q38, Q49, and Q50, which measure analysis and evaluation in English tasks. These tasks required learners to engage in critical reasoning and problem solving, going beyond mere recall (see Fig. 1 and Appendix 1).

Data Analysis

The data were analysed using SPSS version 26 and Mplus software. First, descriptive statistics (mean and standard deviation) were computed to summarise learners’ performance in grammar, LOTS, and HOTS. Pearson’s correlation analysis in SPSS was then employed to examine the strength and direction of associations between grammar knowledge and the two categories of cognitive tasks. Mplus was applied to address construct validity and the predictive power of grammatical knowledge on LOT and HOT. An absolute (Chi-square), two incremental (like CFI/TLI), and a parsimony (RMSEA) fit index has been used to determine if the models accurately represent the underlying constructs and fit the data.

The instruments are valid to assess students’ grammatical knowledge, LOTS and HOTS

The overall instrument demonstrated good internal consistency, with a Cronbach’s alpha of .839 across the 39 items, indicating strong reliability in measuring learners’ grammatical knowledge, LOTS, and HOTS. Complementing the reliability evidence, the model fit indices showed that the data aligned well with the hypothesised structure, χ²(699) = 812.51, p = .002, RMSEA = .035 (90% CI [.022, .045]), CFI = .904, and TLI = .899, all of which fall within the range of acceptable to good fit. Together, these results suggest that the test items not only operate consistently as a measurement tool but also appropriately represent the underlying constructs of grammatical knowledge, lower-order thinking, and higher-order thinking. Therefore, the instrument can be considered both reliable and valid for assessing learners’ performance in this context.

Learners’ performance on grammar-focused items is not related to their performance on lower-order and higher-order thinking tasks

Pearson correlation was conducted to examine the relationship between learners’ performance on grammar-focused items and lower-order thinking tasks and higher-order thinking tasks.

Table 2
Descriptive statistics and Pearson correlations between grammar and lower- and higher-order thinking (N = 134)
Variable	M (%)	SD	1	2
1. Grammar	56.66	28.74
2. Lower-order thinking	82.01	18.91	n.s.
3. Higher-order thinking	82.33	15.66	n.s.	.643**
Note. n.s.: non-significant, ** p < .001 (two-tailed).

Based on the descriptive and correlational analysis, participants demonstrated high performance on both lower-order thinking (M = 7.38, SD = 18.91, 82.01%) and higher-order thinking (M = 12.35, SD = 15.66, 82.33%) tasks. Students scored lower in grammar (M = 8.49, SD = 28.74, 56.66%) compared to LOTS (t(133) = 2.90, p = .004) and HOTS (t(133) = -9.30, p < .001). These results indicate that learners achieved substantially weaker outcomes on grammar-focused items compared to cognitive tasks. The correlation analysis reveals that grammar knowledge was not directly associated with either lower-order or higher-order thinking skills. However, there was a strong, statistically significant positive relationship between lower-order and higher-order thinking (r = .643, p < .001), indicating that individuals who performed well on one type of order thinking task tended to perform well on the other.

Achievement in grammar knowledge predicts learners’ lower-order, and higher-order cognitive skills and the potential of LOTS as a mediator

The structural regression paths provided further insights into the predictive power of grammar knowledge across cognitive domains. Grammar knowledge exhibited a modest positive effect on LOTS, with a standardised coefficient of β = .287, suggesting that learners with stronger grammar knowledge performed better on tasks requiring remembering, understanding, and applying grammatical rules. Similarly, grammar knowledge also predicted HOTS, though with a slightly weaker coefficient (β = .238). A very strong correlation emerged between LOTS and HOTS (β = .873), highlighting that learners’ success in higher-order cognitive tasks is heavily dependent on their ability to master lower-order tasks (See Table 3 and Fig. 2). This suggests that LOTS have the potential as a mediating mechanism between grammar knowledge and HOTS performance, emphasising the sequential nature of cognitive skill development where foundational knowledge is essential for advanced reasoning (Fig. 3).

Table 3
Predicting cognitive performances from grammar knowledge (N = 134)
Predictor	Dependent Variable	Estimate (β)	Interpretation
Grammar	LOTS	.287	Grammar positively predicts LOTS tasks
Grammar	HOTS	.238	Grammar modestly predicts HOTS tasks
LOTS with HOTS		.873	Strong correlation between LOTS and HOTS
Note. LOTS = Lower-Order Thinking; HOTS = Higher-Order Thinking.

According to Fig. 2, the model fit indices showed that the data aligned well with the hypothesised structure, χ²(699) = 812.51, p = .002, RMSEA = .035 (90% CI [.022, .045]), CFI = .904, and TLI = .899, all of which fall within the range of acceptable to good fit.

According to Fig. 3, the indirect pathway from grammar to HOTS via LOTS was therefore substantial, suggesting that grammar knowledge may contribute to higher-order cognitive performance primarily through its effect on lower-order skills. Model fit indices indicated a good fit (CFI = 0.906, TLI = 0.900, RMSEA = 0.035, 90% CI [0.022, 0.045], probability RMSEA ≤ .05 = 0.996), lending statistical support to the mediating model.

The used instruments are valid to assess students’ grammatical knowledge, LOTS and HOTS

The instrument employed to assess grammatical knowledge, LOTS, and HOTS was both reliable and valid. Beyond reliability, the validation of the instrument through confirmatory analysis further strengthens the study. The results indicated that the proposed three-factor structure, grammar, LOTS, and HOTS, was an appropriate representation of the data. This alignment demonstrates that the test items meaningfully differentiated between basic language knowledge and the more complex cognitive knowledge.

The validation of the test is particularly important in contexts such as higher vocational education, where students are required to bridge foundational grammatical knowledge with increasingly complex reasoning tasks. By establishing the reliability and validity of the instrument, this study not only supports the interpretation of the present results but also contributes a tool that may be adapted for future research on language learning and cognitive skill development.

Learners’ performance on grammar-focused items is not directly related to their performance on both lower-order and higher-order cognitive tasks

The findings indicated that there was no significant correlation between learners’ grammar knowledge and their performance on LOTS or HOTS. This suggests that grammatical knowledge does not directly determine learners’ outcomes in cognitive tasks. These results differ from earlier studies, such as those by Muter et al. (2004) and literature reviews analysed by Hjetland et al. (2020) and Jago et al. (2025), which highlighted positive associations between grammar and cognitive performance.

Although learners with stronger grammar knowledge can provide a foundational support for basic language-related cognitive tasks (Aro, 2009), the present findings highlight that grammar may function indirectly. Instead of exerting a direct effect on LOTS or HOTS, grammar might facilitate cognitive engagement through other skills, such as vocabulary or comprehension (Ünaldı & Yüce, 2021). In addition, higher-order tasks such as analysis, evaluation, and critical thinking rely less on grammatical knowledge and more on reasoning (Paulsen & Kolstø, 2022), inference (Acierno et al., 2025), and problem-solving abilities (Koçoğlu & Kanadlı, 2025; Wang et al., 2024).

Regarding the correlation between LOTS and HOTS, on the other hand, the current research found a correlation between the two types of comprehension. This is consistent with previous findings by Jansen & Möller (2022), who studied 36 pre-service teachers. The study found a correlation between the quality of LOTS and HOTS. This strong positive correlation between lower-order and higher-order thinking skills suggests that learners who perform well in basic cognitive tasks may also excel in more advanced thinking skills (Zohar & Dori, 2003).

Achievement in grammar knowledge predicts learners’ lower-order, and higher-order cognitive skills and the potential of LOTS as a mediator

Grammatical knowledge predicts lower- and higher-order thinking performance. Grammatical competence provides the necessary foundational syntactic (Gan, 2024) and structural awareness for tasks (Deng et al., 2022) such as identifying information (Zhang & Tong, 2025), recognising patterns, and applying straightforward rules (Jiang & Su, 2025). These skills facilitate engagement with lower-order tasks, including remembering, understanding and applying knowledge.

With regard to the higher-order thinking tasks, grammar instruction can also encourage critical thinking (Van Rijt & Coppen, 2021). These include metacognition, contextual interpretation, and abstract reasoning (Liu et al., 2024). Background knowledge, motivation, problem-solving strategies and general intelligence play a more substantial role in shaping learners’ skills to perform well in advanced, cognitively demanding contexts (Li et al., 2023). These findings have important implications for language education and assessment. It is therefore suggested that grammatical instruction be integrated within richer contextually embedded tasks that require analysis and evaluation.

The indirect pathway from grammar to HOTS via LOTS was therefore substantial (see Fig. 3). This finding enriches the understanding of how grammatical competence interacts with cognitive skill development. Although grammar knowledge is not directly predictive of HOTS, it plays a foundational role in scaffolding cognitive processes that later facilitate higher-order reasoning. In other words, LOTS may operate as the “bridge” that channels grammatical knowledge into more complex domains of analysis, evaluation, and synthesis. A pattern resonates with Bloom’s hierarchical view of cognitive skills, where mastery of basic forms of knowledge is a prerequisite for higher levels of critical engagement. This mediation pathway provides an important theoretical and pedagogical implication. From a pedagogical perspective, the findings suggest that instructional approaches emphasising grammar as a tool for enhancing LOTS may indirectly strengthen students’ HOTS. From a research perspective, the result points to the value of integrating mediation models in studies that examine the cognitive role of linguistic knowledge.

Limitation

One limitation of this study is the characteristics of the sample. As the participants were drawn from a single group of vocational higher education students, the findings may not be generalisable to broader populations. Learners in other educational contexts, such as academic universities, secondary schools, or adult language learning programmes, may exhibit different patterns of relationships between grammatical knowledge and cognitive performance.

A further limitation lies in the measurement of constructs. Grammar knowledge and cognitive skills were assessed using multiple-choice tests. While this is practical for large-scale testing, it may not capture the full complexity of learners’ language proficiency or cognitive skills.

Finally, the study did not incorporate longitudinal or intervention-based designs, which would allow for stronger claims to be made about developmental trajectories or instructional effects. A cross-sectional dataset only provides a snapshot of learners’ abilities, making it difficult to determine how grammar knowledge supports the progression from lower-order to higher-order thinking skills over time. Future research could employ experimental or longitudinal methodologies to explore how targeted grammar instruction might enhance not only immediate test performance but also broader cognitive and academic outcomes.

Grammar knowledge was not directly correlated with learners’ LOTS or HOTS performance. However, it significantly predicted their lower- and higher-order thinking performance. This indicates that grammar provides the essential syntactic and structural building blocks necessary for basic cognitive operations such as information identification, pattern recognition, and rule application, skills that are fundamental to LOTS. However, the absence of a direct correlation with HOTS reveals that advanced cognitive functions like critical analysis, evaluation, and synthesis operate beyond the scope of grammatical proficiency alone. Instead, the relationship between grammatical knowledge and advanced cognitive performance is fully mediated through LOTS, suggesting that grammar acts not as a direct determinant, but as an enabling factor that scaffolds the development of critical thinking. In other words, grammatical competence creates the necessary conditions for lower-order processing, which in turn provides the cognitive groundwork upon which higher-order reasoning can be constructed. This mediation effect underscores a hierarchical model of skill development, where grammatical knowledge facilitates basic cognitive tasks, includes LOTS, which then serve as the critical pathway to more complex tasks involving HOTS.

Author Contributions

IWEDR: Conceptualised the study, designed the methodology, conducted data collection and analysis, and drafted the original manuscript.

GM: Contributed to the conceptual framework, supervised the research process, provided critical revisions to the manuscript, and approved the final version for submission.

Funding

This research was fully funded by the University of Szeged, Hungary.

Ethics Approval and consent to participate

This study complied with ethical guidelines for research involving human participants, including the principles outlined in the Declaration of Helsinki. The ethical approval was obtained from the Institutional Review Board Doctoral School of Education at the University of Szeged, Hungary.

Informed consent

The participants were inform that the data were anonymous. The research was explained for the study’s purpose, underlined confidentiality and noted that participation was voluntary.

Acierno, J., Kennedy, C., Cushman, F., & Phillips, J. (2025). Inverse option generation: Inferences about others’ values based on what comes to mind. Cognition, 264, 106238. https://doi.org/10.1016/j.cognition.2025.106238
Alkhateeb, A., & Albahr, A. (2025). Integration of Massive Open Online Courses (MOOCs) in Teaching English Grammar in Tertiary Education. International Journal of Computer-Assisted Language Learning and Teaching (IJCALLT), 15(1), 1–14. https://doi.org/10.4018/IJCALLT.378309
Anderson, L. W., & Krathwohl, D. R. (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom’s taxonomy of educational objectives: Complete edition. Addison Wesley Longman, Inc.
Aro, M. (2009). Speakers and doers: Polyphony and agency in children’s beliefs about language learning (Issue 116). University of Jyväskylä.
Chomphooyod, P., Suchato, A., Tuaycharoen, N., & Punyabukkana, P. (2023). English grammar multiple-choice question generation using Text-to-Text Transfer Transformer. Computers and Education: Artificial Intelligence, 5, 100158. https://doi.org/10.1016/j.caeai.2023.100158
Davis, J. (2009). Rule and Meaning in the Teaching of Grammar. Language and Linguistics Compass, 3(1), 199–221. https://doi.org/10.1111/j.1749-818X.2008.00119.x
Deng, Z., Uccelli, P., & Snow, C. (2022). Diversity of Advanced Sentence Structures (DASS) in writing predicts argumentative writing quality and receptive academic language skills of fifth-to-eighth grade students. Assessing Writing, 53, 100649. https://doi.org/10.1016/j.asw.2022.100649
Donnelly, S., Kidd, E., Verkuilen, J., & Rowland, C. (2025). The separability of early vocabulary and grammar knowledge. Journal of Memory and Language, 141, 104586. https://doi.org/10.1016/j.jml.2024.104586
Gan, Q. (2024). Different registers, different grammars in second language production? The dative alternation in spoken and written Chinese learner English. Lingua, 309, 103790. https://doi.org/10.1016/j.lingua.2024.103790
Hjetland, H. N., Brinchmann, E. I., Scherer, R., Hulme, C., & Melby-Lervåg, M. (2020). Preschool pathways to reading comprehension: A systematic meta-analytic review. Educational Research Review, 30, 100323. https://doi.org/10.1016/j.edurev.2020.100323
Ho, Y.-Y. C. (2020). Communicative language teaching and English as a foreign language undergraduates’ communicative competence in Tourism English. Journal of Hospitality, Leisure, Sport & Tourism Education, 27, 100271. https://doi.org/10.1016/j.jhlste.2020.100271
Jago, L. S., Monaghan, P., Alcock, K., & Cain, K. (2025). The effect of preschool vocabulary and grammar on early reading comprehension and word reading: A systematic review and meta-analysis. Educational Research Review, 100680. https://doi.org/10.1016/j.edurev.2025.100680
Jansen, T., & Möller, J. (2022). Teacher judgments in school exams: Influences of students’ lower-order-thinking skills on the assessment of students’ higher-order-thinking skills. Teaching and Teacher Education, 111, 103616. https://doi.org/10.1016/j.tate.2021.103616
Jiang, F. K., & Su, H. (2025). Exemplification and its local grammar patterns in English as an academic lingua franca in research writing. Journal of English for Academic Purposes, 75, 101504. https://doi.org/10.1016/j.jeap.2025.101504
Khalili, T., Ketabi, S., Pnevmatikos, D., & Mahabadi, D. N. A. (2024). Critical thinking and L2 learning in the persian context: A Meta-analysis. Thinking Skills and Creativity, 54, 101640. https://doi.org/10.1016/j.tsc.2024.101640
Koçoğlu, A., & Kanadlı, S. (2025). Critical thinking disposition as a mediator in creativity and problem-solving: A MASEM study. Intelligence, 113, 101951. https://doi.org/10.1016/j.tsc.2024.101640
Krathwohl, D. R. (2002). A revision of Bloom’s taxonomy: An overview. Theory into Practice, 41(4), 212–218. https://doi.org/10.1207/s15430421tip4104_2
Lakew, A. K., Teshome, S., & Negede, D. (2021). Introducing corpus-informed spoken grammar instruction in EFL classrooms: The Ethiopian experience. Corpus Pragmatics, 5(4), 487–510. https://doi.org/10.1007/s41701-021-00106-3
Li, W., Huang, J.-Y., Liu, C.-Y., Tseng, J. C., & Wang, S.-P. (2023). A study on the relationship between student’learning engagements and higher-order thinking skills in programming learning. Thinking Skills and Creativity, 49, 101369. https://doi.org/10.1016/j.tsc.2023.101369
Liu, J., Liu, Z., Wang, C., Xu, Y., Chen, J., & Cheng, Y. (2024). K-12 students’ higher-order thinking skills: Conceptualization, components, and evaluation indicators. Thinking Skills and Creativity, 52, 101551. https://doi.org/10.1016/j.tsc.2024.101551
McCarthy, K. S., Roscoe, R. D., Allen, L. K., Likens, A. D., & McNamara, D. S. (2022). Automated writing evaluation: Does spelling and grammar feedback support high-quality writing and revision? Assessing Writing, 52, 100608. https://doi.org/10.1016/j.asw.2022.100608
Mirosław, P., Derakhshan, A., Mehdizadeh, M., & Kruk, M. (2023). Yet another look at strategies for learning grammar: Validating the Grammar Learning Strategy Inventory in the Iranian EFL context. System, 118, 103139. https://doi.org/10.1016/j.system.2023.103139
Muter, V., Hulme, C., Snowling, M. J., & Stevenson, J. (2004). Phonemes, rimes, vocabulary, and grammatical skills as foundations of early reading development: Evidence from a longitudinal study. Developmental Psychology, 40(5), 665. https://doi.org/10.1037/0012-1649.40.5.665
Nateghian, N. (2024). English language needs of Iranian students of civil engineering: Are the courses aligned with workplace needs? English for Specific Purposes, 76, 122–135. https://doi.org/10.1016/j.esp.2024.08.002
Newmann, F. M. (1990). Higher order thinking in teaching social studies: A rationale for the assessment of classroom thoughtfulness. Journal of Curriculum Studies, 22(1), 41–56. https://doi.org/10.1080/0022027900220103
Pacheco, C. S., & Herrera, C. I. (2021). A conceptual proposal and operational definitions of the cognitive processes of complex thinking. Thinking Skills and Creativity, 39, 100794. https://doi.org/10.1016/j.tsc.2021.100794
Paulsen, V. H., & Kolstø, S. D. (2022). Students’ reasoning when faced with test items of challenging aspects of critical thinking. Thinking Skills and Creativity, 43, 100969. https://doi.org/10.1016/j.tsc.2021.100969
Pawlak, M. (2013). Researching grammar learning strategies: Combining the macro-and micro-perspective. In Perspectives on foreign language learning (pp. 193–211). Wydawnictwo Uniwersytetu Łódzkiego. https://doi.org/10.18778/7969-032-9.15
Pawlak, M. (2020). Grammar learning strategies as a key to mastering second language grammar: A research agenda. Language Teaching, 53(3), 358–370. https://doi.org/10.1017/S0261444819000314
Ramírez-Montoya, M. S., Castillo-Martínez, I. M., Sanabria-Z, J., & Miranda, J. (2022). Complex thinking in the framework of education 4.0 and open innovation—A systematic literature review. Journal of Open Innovation: Technology, Market, and Complexity, 8(1), 4. https://doi.org/10.3390/joitmc8010004
Robertson, M., Macdonald, S., Starks, D., & Nicholas, H. (2018). Enabling change in EFL teachers’ ideologies about grammar and grammar teaching through alternative pedagogies. System, 72, 75–84. https://doi.org/10.1016/j.system.2017.11.002
Rong, X., & Révész, A. (2025). The effects of task complexity on second language writing processes and products in computer-assisted collaborative writing. Journal of Second Language Writing, 69, 101216. https://doi.org/10.1016/j.jslw.2025.101216
Sands, K. R., Monroe, A. J., & Mills, C. M. (2023). “How do fish breathe underwater?”: Young children’s ability to evaluate and remember different types of explanations regarding biological phenomena. Cognitive Development, 66, 101330. https://doi.org/10.1016/j.cogdev.2023.101330
Sato, M., & Oyanedel, J. C. (2019). “I think that is a better way to teach but…”: EFL teachers’ conflicting beliefs about grammar teaching. System, 84, 110–122. https://doi.org/10.1016/j.system.2019.06.005
Su, H. (2025). Critical thinking-embedded EFL translation instruction and its impact on EFL translation learners. Thinking Skills and Creativity, 57, 101827. https://doi.org/10.1016/j.tsc.2025.101827
Teng, Y. (2024). Methods of Improving and Optimizing English Education Level in Higher Vocational Colleges Under the Background of Big Data. International Journal of E-Collaboration (IJeC), 20(1), 1–20. https://doi.org/10.4018/IJeC.345239
Ünaldı, İ., & Yüce, E. (2021). The relationship among vocabulary size, grammar proficiency, and critical thinking skills of adult language learners. Adult Learning, 32(2), 70–78. https://doi.org/10.1177/1045159520959473
Van Rijt, J. H., & Coppen, P.-A. J. (2021). The conceptual importance of grammar: Knowledge-related rationales for grammar teaching. Pedagogical Linguistics, 2(2), 175–199. https://doi.org/10.1075/pl.21008.van
Wang, X.-M., Huang, X.-T., & Zhou, W.-Q. (2024). The effect of university students’ self-efficacy on problem-solving disposition: The chained dual mediating role of metacognition disposition and critical thinking disposition. Thinking Skills and Creativity, 54, 101658. https://doi.org/10.1016/j.tsc.2024.101658
Wijnands, A., Rijt, J. van, & Coppen, P.-A. (2021). Learning to think about language step by step: A pedagogical template for the development of cognitive and reflective thinking skills in L1 grammar education. Language Awareness, 30(4), 317–335. https://doi.org/10.1080/09658416.2021.1871911
Wyatt, M., & Dikilitaş, K. (2021). English language teachers’ self-efficacy beliefs for grammar instruction: Implications for teacher educators. The Language Learning Journal, 49(5), 541–553. https://doi.org/10.1080/09571736.2019.1642943
Yeh, Y. (2012). A co-creation blended KM model for cultivating critical-thinking skills. Computers & Education, 59(4), 1317–1327. https://doi.org/10.1016/j.compedu.2012.05.017
Youjun, T., & Xiaomei, M. (2022). Computational thinking: A mediation tool and higher-order thinking for linking EFL grammar knowledge with competency. Thinking Skills and Creativity, 46, 101143. https://doi.org/10.1016/j.tsc.2022.101143
Zhang, L., & Tong, F. (2025). ‘Could you send us your latest catalogue?’: A local grammar of requesting in English business letters. English for Specific Purposes, 79, 43–55. https://doi.org/10.1016/j.esp.2025.04.001
Zohar, A., & Dori, Y. J. (2003). Higher order thinking skills and low-achieving students: Are they mutually exclusive? The Journal of the Learning Sciences, 12(2), 145–181. https://doi.org/10.1207/S15327809JLS1202_1

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The Predictive Role of Grammar Knowledge in Lower- and Higher-Order Thinking Skills within Vocational Education

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Abstract

Figures

Introduction

Theoretical Framework

Grammar Proficiency

Lower-and Higher-Order Thinking

Research Methodology

Research Design

Participants

Procedures

Tests Items and Reliability

Data Analysis

Result

The instruments are valid to assess students’ grammatical knowledge, LOTS and HOTS

Discussion

The used instruments are valid to assess students’ grammatical knowledge, LOTS and HOTS

Limitation

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1