學術論文是一種特殊的文體，有外顯、制式化的結構，如「簡介」、「相關文獻」、「方法」、「結果」、「討論」等。在各節中，又透過所謂文步的隱藏性修辭結構，有條不紊地呈現研究的背景、動機、內容。因此，在學術論文寫作的教學，分析文步扮演了重要的角色。在本論文中，我們提出了一個方法，將所給予的學術論文的每一個句子，標示所隱含的文步（moves），藉以幫助英文非其母語學生，寫作學術論文。我們採取透過常見寫作樣板（common patterns）取得訓練資料的研究路線。而我們的方法涉及擷取常見寫作樣板、標示樣板的文步、產生標示文步的訓練資料、設計分類特徵值、訓練一個文步分類器。在執行時，我們將句子轉換成特徵向量，運用分類器預測句子的文步。我們提出一個雛型系統WriteAhead，應用分類的句子的資料，提示學習者，如何寫作各種文步的句子。

Rhetorical moves are a useful framework for analyzing the hidden rhetorical organization in research papers, in teaching academic writing. We propose a method for learning to classify the moves of a given set sentences in a academic paper. In our approach, we learn a set of move-specific common patterns, which are characteristic of moves, to help annotate sentences with moves. The method involves using statistical method to find common patterns in a corpus of research papers, assigning the patterns with moves, using patterns to annotate sentences in a corpus, and train a move classifier on the annotated sentences. At run-time, sentences are transformed into feature vectors to predict the given sentences. We present a prototype system, MoveTagger, that applies the method to a corpus of research papers. The proposed method outperforms previous research with a significantly higher accuracy.