發(fā)布時(shí)間：2018-04-22 06:02

  本文選題：題向量 + 題向量化模型　； 參考：《計(jì)算機(jī)工程與科學(xué)》2017年10期

【摘要】：隨著互聯(lián)網(wǎng)+教育的深度融合以及移動(dòng)終端上電子習(xí)題的推廣使用,學(xué)生的學(xué)習(xí)過(guò)程數(shù)據(jù)可以被實(shí)時(shí)獲取,充分利用這些過(guò)程數(shù)據(jù),及時(shí)定位學(xué)生的知識(shí)病灶,開(kāi)具有針對(duì)性的輔導(dǎo)處方,實(shí)現(xiàn)知識(shí)的按需推送,對(duì)于減輕學(xué)生的簡(jiǎn)單重復(fù)勞動(dòng),提高學(xué)習(xí)效率將會(huì)產(chǎn)生積極影響。試圖通過(guò)分析在線習(xí)題系統(tǒng)的答題數(shù)據(jù),發(fā)現(xiàn)學(xué)生的知識(shí)掌握規(guī)律,根據(jù)錯(cuò)題的伴生狀況捕獲習(xí)題的相關(guān)性。為此,構(gòu)建了題向量化模型,提出了題向量表示的新方法,設(shè)計(jì)了負(fù)采樣訓(xùn)練算法,并用程序?qū)崿F(xiàn)了上述算法。經(jīng)過(guò)實(shí)際在線系統(tǒng)的相關(guān)數(shù)據(jù)訓(xùn)練,獲得了相應(yīng)題向量,而后利用題向量的向量運(yùn)算,可方便查找相同習(xí)題、相同知識(shí)點(diǎn)習(xí)題以及相近知識(shí)點(diǎn)習(xí)題等,可根據(jù)學(xué)生錯(cuò)題個(gè)案,推斷其知識(shí)掌握的其他薄弱環(huán)節(jié)。
[Abstract]:With the deep integration of Internet education and the popularization of electronic exercises on mobile terminals, students' learning process data can be obtained in real time. It will have a positive effect on lightening the students' simple repeated work and improving the study efficiency by issuing the directed guidance prescription and realizing the knowledge push according to the need. By analyzing the answer data of the online exercise system, this paper attempts to find out the rules of students' knowledge mastery, and to capture the correlation of the exercises according to the concomitant condition of the wrong questions. In this paper, a problem vectorization model is constructed, a new method of problem vector representation is proposed, a negative sampling training algorithm is designed, and the above algorithm is implemented by program. Through the relevant data training of the actual online system, the corresponding problem vectors are obtained, and then the vector operation of the problem vectors is used to find the same exercises, the same knowledge points exercises and the similar knowledge points exercises, and so on. Infer other weaknesses in his knowledge.
【作者單位】： 江蘇師范大學(xué)計(jì)算機(jī)科學(xué)與技術(shù)學(xué)院;
【基金】：國(guó)家自然科學(xué)基金(61402207,61272297) 江蘇省普通高校研究生科研創(chuàng)新計(jì)劃(KYLX15_1454)
【分類號(hào)】：G434;TP311.13
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本文編號(hào)：1785896