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14 pages, 664 KiB

Open AccessArticle

Designing a Digital Game for Chinese Character Learning: A Theory-Driven Practice Approach

by Tingting Wang

Educ. Sci. 2024, 14(12), 1366; https://doi.org/10.3390/educsci14121366 - 12 Dec 2024

Viewed by 1563

Engaging students in Chinese character learning tasks poses significant challenges for instructional design, especially for learners from alphabetic language backgrounds, due to Chinese characters’ complex, morpho-syllabic structure. Traditional teaching methods, such as rote memorization and hand copying, have long dominated instruction but often result in limited task engagement. This study explores a gamified approach to teaching Chinese characters grounded in task engagement principles. Specifically, it examines how task engagement principles could be integrated into a digital game designed for beginner-level students on their understanding of Chinese character structure and engagement in learning tasks. The study details the development process and analyzes quantitative and qualitative data to assess students’ learning outcomes. Findings demonstrate that the Chinese character game significantly improves character recognition and student engagement, fostering collaborative learning and enhancing overall academic performance. This study highlights the importance of incorporating engagement-driven principles and a radical-driven approach into game-based language instruction, offering educators practical insights into creating effective educational tools that blend content with interactive and collaborative elements. Full article

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18 pages, 1964 KiB

Open AccessArticle

Four Secular Ruke Dongba Notes Generated during Fieldwork: An Innovative Language Documentation Approach

by Duoduo Xu

Languages 2023, 8(3), 162; https://doi.org/10.3390/languages8030162 - 30 Jun 2023

Viewed by 1993

Abstract

This paper documents and analyzes several Dongba script notes collected during my interviews with the Ruke Dongba priests. It provides an overview of Ruke Dongba glyphs in processing daily vocabulary and the International Phonetic Alphabet. It compares these Dongba pictographs with the Geba script, the syllabic writing system of Naxi people, as well as the various types of scripts used by some other ethnic groups, which show a general tendency of Romanization in the generation of alphabetic writing systems and provides a pattern inherent in the historical evolution of writing. IPA symbols, a fundamental tool of field linguists, facilitate learners in grasping a language and nonalphabetic scripts. In addition to analyzing the Ruke Dongba pictographs attested in the secular manuscripts in the context of history of writing, this study contributes to the linguistic description of Ruke Dongba culture and the diversity of Dongba tradition. Full article

(This article belongs to the Special Issue New Directions for Sino-Tibetan Linguistics in the Mid-21st Century)

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18 pages, 1710 KiB

Open AccessArticle

Better Word Representation Vectors Using Syllabic Alphabet: A Case Study of Swahili

by Casper S. Shikali, Zhou Sijie, Liu Qihe and Refuoe Mokhosi

Appl. Sci. 2019, 9(18), 3648; https://doi.org/10.3390/app9183648 - 4 Sep 2019

Cited by 6 | Viewed by 4389

Abstract

Deep learning has extensively been used in natural language processing with sub-word representation vectors playing a critical role. However, this cannot be said of Swahili, which is a low resource and widely spoken language in East and Central Africa. This study proposed novel word embeddings from syllable embeddings (WEFSE) for Swahili to address the concern of word representation for agglutinative and syllabic-based languages. Inspired by the learning methodology of Swahili in beginner classes, we encoded respective syllables instead of characters, character n-grams or morphemes of words and generated quality word embeddings using a convolutional neural network. The quality of WEFSE was demonstrated by the state-of-art results in the syllable-aware language model on both the small dataset (31.229 perplexity value) and the medium dataset (45.859 perplexity value), outperforming character-aware language models. We further evaluated the word embeddings using word analogy task. To the best of our knowledge, syllabic alphabets have not been used to compose the word representation vectors. Therefore, the main contributions of the study are a syllabic alphabet, WEFSE, a syllabic-aware language model and a word analogy dataset for Swahili. Full article

(This article belongs to the Section Computing and Artificial Intelligence)

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