A Study Of Mobile Terminal-based Deep Learning Of English Vocabulary

Thanks to mobile technology,mobile terminal-based English vocabulary learning is playing an increasingly important role in English vocabulary learning for its distinctive features,such as ubiquitousness,personalization,interactivity and accessibility.For all the conveniences it has brought about,mobile learning is blamed for the fragmentation of learning on the part of the learner,who is awash with redundant information.Given the lack of time for the integration and internalization of knowledge,the learner engaged in mobile learning is likely to adopt a surface learning method,with which he tends not to delve into the information and construct meaning out of it.However,few studies have yet been conducted to address this problem.In response to it,this study reviewed the researches concerning mobile English vocabulary learning and found that the relevant studies till now mainly focused on the width of vocabulary and paid little attention to the depth and organization of vocabulary.To figure out the feasibility of enhancing deep learning of English vocabulary based on mobile terminals,this dissertation put forward two research questions:Research Question 1: What is the connotation of deep learning of English vocabulary?Research Question 2: In what aspects can the current mobile terminals promote deep learning of English vocabulary?To address the first research question,the studies about the main issues in L2 vocabulary acquisition were reviewed.Also reviewed were the various definitions of deep learning in the science of learning.From the review,the working definition about deep learning is generalized,that is,deep leaning is the process in which the learner adopts higher order thinking skills including metacognition to actively engage in meaning construction.And then the framework of vocabulary competence was integrated into the concept so that the connotation of deep learning of English vocabulary was arrived at: deep learning of English vocabulary is the process in which the learner adopts higher order thinking skills including metacognition to construct meanings out of the vocabulary building materials,with the purpose of developing the network of mental lexicon to promote his vocabulary competence.Research Question 2 was subdivided into 4 questions:Question 2.1 What are the strengths and deficiencies of the current mobile terminals in promoting deep learning of English vocabulary?Question 2.2 How much time has the learner contributed to mobile vocabulary learning?Question 2.3 What is the ultimate purpose of the learner's using English learning mobile terminals?Question 2.4 From the learner's perspective,to what extent have the English learning mobile terminals contributed to the enhancing of deep learning of English vocabulary?To address Question 2.1,12 target words were randomly selected from Nation(1990)L2 Word Frequency List and were learnt in 5 mobile terminal-based softwares intended for vocabulary learners.The study found that they did promote deep learning of English vocabulary in one or more of such aspects as learning management,motivating,multiple representation of knowledge,hypertext,knowledge visualization and social learning network.However,deficiencies were found in: 1)personalized learning;2)the coverage of depth of vocabulary;3)the access to meta-knowledge of vocabulary;4)the assessment of productive skills;5)the inclusion of assessment intended for other dimensions of vocabulary knowledge than vocabulary size.The survey with the questionnaire led to the following findings:1)The questionnaire takers spent in learning vocabulary through mobile terminals on average half the time they spent in vocabulary learning as a total.2)Over 70% questionnaire takers thought that they chose mobile vocabulary learning mainly to grasp different meanings of a word in different contexts or use it flexibly,while no more than 30% questionnaire takers focused merely on vocabulary enlargement.It suggested the learner's great need for vocabulary competence enhancement.3)The current vocabulary learning mobile terminals performed fairly well in enlarging the learner's vocabulary,but undesirably in helping him promot deep learning aimed at vocabulary competence enhancement.By integrating the research findings,this dissertation provided the suggestions on promoting mobile terminal-based deep learning of English vocabulary,which are as follows:To build ontology of vocabulary knowledge within a certain range so that the dimensions of vocabulary knowledge,such as phonetic and semantic features,can be well organized;To represent and visualize learning materials in multiple ways via various modes of media and provide the learner with an opportunity to visualize their thinking with visual aids;To offer the learner a social network of learning,where,by adopting higher order thinking skills,he can observe and discover other learners' performances,and cooperate with them;To track and record the learner's learning behavior and performance;To reinforce the learner's desirable learning behavior and offer him immediate cognitive and emotional feedbacks;To enable the learner to build and refine his mental lexicon network,enhance his receptive and productive skills,build upon his meta-knowledge of vocabulary and develop his metacognition,so that he can take the initiative to discover and internalize vocabulary in richer and more authentic English contexts,thereby honing his deep learning skills in this regard.The dissertation is creative in the following aspects: firstly,it shed new light on L2 vocabulary acquisition by adopting an integrated perspective of mobile learning,L2 vocabulary acquisition and deep learning;secondly,it redefined the meta-knowledge of vocabulary as the knowledge of vocabulary knowledge,which functions as a schematic framework of reference to guide vocabulary learning;thirdly,it offered approaches to the mobile terminal-based deep learning of English vocabulary,thus contributing to the building of an integrated on-line English vocabulary learning platform.The limitations of this study include: 1)the possible biases in examining the target mobile terminal-based softwares merely through the author's observations,despite the attempts to make the research more objective by conducting it on the basis of the quantitative data;2)the lack of follow-up interviews of some of the questionnaire takers for further and more elaborate information on their learning experiences and obseravtions of mobile terminal-based vocabulary learning.To deepen our understanding of mobile terminal-based deep learning of English vocabulary,further studies are expected to focus on quasi experiments on the effectiveness of mobile terminal-based softwares in promoting deep learning of English vocabulary by clarifying the interactions between learner factors such as learner needs,learning style,prior vocabulary competence and engagement,and mobile terminal-based vocabulary learning environments such as technical support and learning materials organization.Further efforts can thus be made to optimize the framework of mobile terminal-based softwares to engage the learner in deeper learning of English vocabulary.