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Data · dataset · 2026

Breaking the shackles of rote learning: towards a transformative ELT pedagogy in a Saudi University English language programme

Listed in ZivaHub and Deakin Research Online and DMU Figshare and UCL Research Data Repository — shown once because both records carry DOI 10.17034/32631390.v1

Saudi Arabia recently joined the G20 world emerging economies and in 2016 launched its 2030 Vision to diversify its economy away from oil dependency.

Description

The vision stresses that the current educational system must align with future market needs and that reform is paramount to nurture a generation of independent and skilled graduates with good communication skills where English plays an integral role. However, despite the efforts of English language programmes in universities and schools to adopt communicative teaching approaches to English language learning, rote learning persists.

The English Language Institute (ELI) at Star University (pseudonym) in Saudi Arabia, the site of this study, encourages rote learning because it has to adhere to pacing guides, follow pre-selected textbooks, and conduct multiple English quizzes and tests throughout the seven-week module in the preparatory year programme (PYP), also called foundation program. Rote learning has led to what I define as ‘inflexible retentiveness’ (IR) which impedes learners’ progression in different aspects of language acquisition. <br><br>Set against Dörnyei’s (2005) theory of second language (L2) motivational self-system model, this empirical research explored how flipped learning (FL) could improve 25 Star University (SU) EFL students’ engagement, autonomous learning and self-conceptions in the acquisition of English, and whether FL could discourage and/or complement rote learning.

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A seven-week intervention was designed using a mixed methodology approach to generate the data using a) institutional documents to identify the root problems (i.e., historical context) of the overreliance on rote learning; b) students’ writing samples to assess the language development over the course of the intervention; c) students’ conversations in WhatsApp and the virtual classroom to provide alternative teaching and learning platforms to trigger engagement and promote autonomous learning environment, and; d) a questionnaire to generate qualitative and quantitative data to uncover students’ perceptions of self. <br><br>Evidence from the triangulated data shows that majority of participating EFL students were more motivated, became more autonomous in their learning and gained greater self-concept using various ICT (Information and Communication Technologies) platforms than they had been when rote learning was the principal pedagogic method.

FL was favoured over rote learning strategies by the majority of students. FL also reduced students’ cognitive load which had had negative effects on task comprehension and completion. Greater student agency was demonstrated in multiple tasks and in their efforts to meet deadlines.

Exam results showed that participating students scored above average compared to their peers from other sections. <br><br>This research study offers an alternative ELT pedagogy to the entrenched traditional lecture-based instruction and demonstrates that the flipped learning model could help meet the 2030 vision goals. It has implications for both EFL learners and teachers and is of interest to the policymakers in English language departments.

However, to make the desired changes to English language teaching, learning and motivation, the right environment should be in place and on-the-job training is required for EFL teachers before they can embark on such a transition. Technological Pedagogical Content Knowledge (TPACK) model elements should be considered as the starting point to deliver a successful FL model.

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Where it is published

Catalogue records · 1

Topics

Inferred from text
Linguistics 70%
Provenance · 4 source records, 13 field assertions
SourceKeyLast seenRaw
ZivaHuboai:figshare.com:article/326313907 d agoJSON v1
Deakin Research Onlineoai:figshare.com:article/326313907 d agoJSON v1
DMU Figshareoai:figshare.com:article/326313907 d agoJSON v1
UCL Research Data Repositoryoai:figshare.com:article/326313907 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].anzsrc:group:4704enrichment · zivahub uct ac zataxonomy-embedding@1.1.0title+keywords+description (70%)
concepts[field].local:field:earth-environmentalmapping · dro deakin edu auconnector:dro_deakin_edu_au@1.0.0
concepts[field].local:field:earth-environmentalmapping · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
concepts[field].local:field:earth-environmentalmapping · figshare dmu ac ukconnector:figshare_dmu_ac_uk@1.0.0
concepts[field].local:field:earth-environmentalmapping · rdr ucl ac ukconnector:rdr_ucl_ac_uk@1.0.0
concepts[field].local:field:humanitiesmapping · zivahub uct ac zaconnector:zivahub_uct_ac_za@1.0.0
concepts[field].local:field:humanitiesmapping · dro deakin edu auconnector:dro_deakin_edu_au@1.0.0
concepts[field].local:field:humanitiesmapping · rdr ucl ac ukconnector:rdr_ucl_ac_uk@1.0.0
concepts[field].local:field:humanitiesmapping · figshare dmu ac ukconnector:figshare_dmu_ac_uk@1.0.0
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