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Record W3111669088 · doi:10.5430/ijhe.v10n2p253

Trials of the Islamic Education Learning Model in Indonesian Universities: A Sufistic Approach as An Alternative

2020· article· en· W3111669088 on OpenAlexvenueno aff
Munawar Rahmat, Muhammad Yahya

Bibliographic record

VenueInternational Journal of Higher Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and Radicalism
Canadian institutionsnot available
FundersKementerian Riset dan Teknologi /Badan Riset dan Inovasi NasionalUniversitas Pendidikan IndonesiaBadan Riset dan Inovasi Nasional
KeywordsPrayerIslamSufismMeaning (existential)ShariaPsychologyIndonesianSociologyReligious studiesTheologyEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

The students of Indonesia University of Education (UPI) and Bandung Islamic University (UNISBA) typically practice religion as it was received from their parents and socio-religious environment. They Salat, which is the main prayer of Islam, simply abort their obligations, and after praying, immediately leave their prayer mats without making dhikr or remembering God first. Furthermore, they do not understand khushu` Salat, which involves remembering God throughout the prayer, along with the meaning of dhikr, and the importance of a Murshid, which is the Grand Shaykh of Sufi Order. They also view Sufism as non-Islamic teaching and are cynical about the practitioners. Therefore, this study aims to examine the effectiveness of the Sufistic learning model in Islamic Religious Education to improve students’ understanding of these teachings in a substantive and tolerant manner. This research used an R&D approach, and the stage that was performed involved the preparation of a draft model and associated trials. Meanwhile, the learning used the madhhab typology approach of the Sufi and Shari`a Islamic models. The trial results showed that the Sufistic approach was effective in increasing students’ understanding of Islamic teachings in a substantive and tolerant manner. Before learning, students were unaware of Sufi Islam and viewed it as a foreign influence. Also, they did not understand khushu` prayers, comprehend the importance of dhikr, nor that of learning from Murshid. After learning, they understood Sufism, accepted the teachings and did not consider them to be foreign influences, and also recognized Islam in a substantive and tolerant manner. Therefore, the Sufism approach is improving the quality of religion and tolerance of students, with the implication that the model is an alternative in learning Islamic education at universities.Objective: This study aims to examine the effectiveness of the Sufistic learning model in Islamic Religious Education to improve students’ understanding of Islamic teachings in a substantive and tolerant manner.Methods: A research and development (R&D) approach, which was performed in the preparation of a draft model and associated trials, was used. Meanwhile, the learning employed the madhhab typology approach of the Sufi and Shari`a Islamic model.Results: The trial results showed that the Sufistic approach in Islamic Education was effective in increasing students’ understanding of Islamic teachings in a substantive and tolerant manner. Before learning, students unfamiliar with Sufi Islam, saw it as a foreign influence, and did not understand khushu` Salat, which involves remembering God throughout the prayer. Also, they considered dhikr, which means to remember God, and learning from Murshid as unimportant. However, they understood Sufism, accepted it as Islamic teachings and not foreign influences, and recognized the religion in a substantive and tolerant manner after the learning process.Conclusion: The Sufism approach in Islamic Education has succeeded in improving the quality of religion and tolerance of students.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.029
metaresearch head score (Gemma)0.040
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.156

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.040
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0040.004
Open science0.0030.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.044
GPT teacher head0.382
Teacher spread0.338 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2020
Admission routes1
Has abstractyes

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