基于SPOC論壇的學習社交網(wǎng)絡分析
發(fā)布時間:2018-04-25 00:03
本文選題:SPOC + 社會網(wǎng)絡分析; 參考:《華中師范大學》2017年碩士論文
【摘要】:目前,隨著信息技術(shù)與教育教學的深度融合,越來越多的大學正在將在線學習環(huán)境整合到各類課程中,與傳統(tǒng)課堂相比,在線學習不僅增加了學習者參與課程的積極性,而且有利于實現(xiàn)協(xié)作學習、交互學習,對于改善學習進程、優(yōu)化學習效果具有重要意義。為了引導在線學習群體向更高效的狀態(tài)轉(zhuǎn)變,在線教育的研究者也正在尋求有效的學習激勵機制,吸引更多學生積極參與課程學習,提升課堂活躍度和教學質(zhì)量,以提高學習者的學習成功率。此外,在大數(shù)據(jù)浪潮下,MOOC以自身的優(yōu)勢得到了快速發(fā)展,但在實踐中也發(fā)現(xiàn)MOOC具有很多不足,因此促使了一種更適宜學校教育的教育模式的出現(xiàn)——SPOC。SPOC環(huán)境下,課程參與者通過交互形成了一個學習網(wǎng)絡,網(wǎng)絡中的節(jié)點代表課程參與者,參與者通過交互使知識得以傳播、建構(gòu)。面對SPOC教學模式的規(guī);l(fā)展,為了系統(tǒng)、有效地識別出影響在線學習環(huán)境中有效學習發(fā)生的主要影響因素,急需采用新的研究方法來分析在線學習群體的學習行為方式。本文通過對華中師范大學云課堂平臺上《文學翻譯》課程的論壇討論區(qū)進行數(shù)據(jù)采集,采用社會網(wǎng)絡分析、內(nèi)容分析和相關分析方法,分析在線學習者在互動討論中形成的社會網(wǎng)絡位置信息與學習成效之間的相關性,以及參與者論壇交互的知識建構(gòu)水平情況與學習者在網(wǎng)絡中的位置之間的相關性。研究結(jié)果表明,在線論壇區(qū)中,學習成效高的學習者趨于同學習成效低的學習者建立交互聯(lián)系,而學習者的社會網(wǎng)絡中心性與學習成效之間呈現(xiàn)顯著的正相關性,且學習成效高的學習者往往具有更高的聲望和影響力,同時處于核心的學習者其學習成效越高。但是,也得到結(jié)論,論壇參與者的知識建構(gòu)水平層級分布不高,且其與學習者在交互網(wǎng)絡中的位置、學習成效之間并無明顯的相關性。
[Abstract]:At present, with the deep integration of information technology and education and teaching, more and more universities are integrating the online learning environment into various courses. Compared with the traditional classroom, online learning not only increases the enthusiasm of learners to participate in the course. Moreover, it is beneficial to realize cooperative learning and interactive learning, which is of great significance to improve the learning process and optimize the learning effect. In order to guide online learning groups to a more efficient state of change, online education researchers are also looking for an effective learning incentive mechanism to attract more students to actively participate in curriculum learning, improve classroom activity and teaching quality. In order to improve learners' learning success rate. In addition, under the tide of big data, MOOCs have developed rapidly with their own advantages, but in practice, they also find that MOOC has many shortcomings, so it promotes the emergence of a more suitable educational model for school education, which is in the environment of SPOC.SPOC. Curriculum participants form a learning network through interaction, the nodes in the network represent course participants, and participants communicate and construct knowledge through interaction. In the face of the large-scale development of SPOC teaching mode, in order to identify the main influencing factors of effective learning in the online learning environment effectively, it is urgent to adopt new research methods to analyze the learning behavior of online learning groups. This paper collects data from the discussion area of Literature Translation on the cloud classroom platform of Central China normal University, and adopts the methods of social network analysis, content analysis and related analysis. This paper analyzes the correlation between the social network location information formed by online learners during the interactive discussion and their learning performance, and the correlation between the level of knowledge construction of participants' forum interaction and the learners' position in the network. The results show that, in the online forum, learners with high learning efficiency tend to establish interaction with those with low learning performance, and there is a significant positive correlation between learners' social network-centeredness and learning effectiveness. Learners with high learning effectiveness tend to have higher prestige and influence, and learners at the core have higher learning effectiveness. However, it is also concluded that the level of knowledge construction of forum participants is not high, and there is no obvious correlation between the level of knowledge construction and the position of learners in the interactive network and learning effectiveness.
【學位授予單位】:華中師范大學
【學位級別】:碩士
【學位授予年份】:2017
【分類號】:I046-4;G434
【參考文獻】
相關期刊論文 前9條
1 劉三;石月鳳;劉智;彭f[;孫建文;;網(wǎng)絡環(huán)境下群體互動學習分析的應用研究——基于社會網(wǎng)絡分析的視角[J];中國電化教育;2017年02期
2 鄭勤華;李秋R,
本文編號:1798843
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