《臺大華語文學習與科技》學術出版品由臺灣大學華語教學碩士學位學程創刊，是以漢語本體研究、語料庫分析、外語習得歷程、認知心理學、師資培訓等領城為研究對象之專業學術刊物，創刊號於2021年十二月出刊。
《臺大華語文學習與科技》期刊每年出版一卷，每卷兩期，六月和十二月出刊，同時收錄正體中文及英文稿件並為開放取用期刊，所有文章皆可自由下載。

創刊理念：
法國哲學家孔德（Auguste Comte）於十九世紀初期提出，應運用科學方法來進行社會科學之研究，開啟了實證研究（positive research）的濫觴；以客觀實驗證明一個假設之真偽、進而建構事件的因果關係，也成為後起的實徵研究（empirical research）之主要精神：透過大膽假設、統計歸納等方法得出通則，並可推論至具有同根情境之其他狀況。以漢語本體研究為本，「華語文教學」結合語言本體研究、語料庫分析、外語習得、認知心理學等領域，為落實實徵研究的最佳學術領域。
而從1980年代末期，語言學習引進了機器學習演算法，自然語言處理（natural Language processing）產生了重大革新。史丹福大學自然語言小組的研究人員，開發了一系列的自然語言分析工具，如Stanford parser，將語法和自然語言分析進一步結合，推動了語言學理論和自動語法分析的實踐。
量化研究之趨勢也為第一線華語教學帶來了全新的風貌。新型教學法的測試，抑或師資培訓的過程，皆可透過大數據之分析，找到最合適的教學法和事半功倍的師培模式，進而提供學習者最佳的學習方式。
無論是以實徵研究為基礎的客觀實驗，近三十年興起的自然語言分析，或是不同教學法的成效探討，皆以量化分析為本，讓數字說話。基於以上認知，本刊徵求與華語文相關之語料庫研究、認知心理實驗、行動研究等論文，探面向可觸及語法、語義、語用、語音、教學法等層面，優先審理從量化角度處理語料之相關研究，也保持華語教學和各領域對話的可能性。

Chinese Language Learning and Technology (CLLT) is a peer-reviewed, biannual journal, published by the Graduate Program of Teaching Chinese as a Second Language at National Taiwan University, Taiwan. The journal welcomes articles using corpus-based analytical techniques as well as experimental methods to address a range of issues in the teaching and learning of Mandarin Chinese as a Second Language. Topics of interest include, but are not limited to, the following: corpus linguistics, cognitive linguistics, Language pedagogy, and Language acquisition. All our content is open access: anyone can read everything published for free, without the need to subscribe, and there are no article processing charges (APCs) or submission fees.

The overall aim of this journal is to provide a forum for researchers and Chinese Language educators to publish research and communicate ideas that have direct relevance and impact on Teaching Chinese as a Second Language.

The second issue will appear in December 2021, and the deadline for submission is 31 May 2021. We welcome papers written in traditional Chinese (not exceeding 25,000 words) and English (single-spaced and within 35 pages). All information regarding the author or authors, including name, affiliation, contact information, and acknowledgements should be removed. Submission should be sent to the following e-mail address: ntutcsljr@gmail.com