基于層次分析法和KH-KELM的英語教學質(zhì)量評價

朱玥

摘 要：為了實現(xiàn)英語教學質(zhì)量評價，客觀地反映英語教學質(zhì)量水平，運用層次分析法構建了一套基于教師素質(zhì)、教學態(tài)度、教學內(nèi)容、教學方法和教學效果的英語教學質(zhì)量評價指標體系。將英語教學質(zhì)量水平劃分為欠規(guī)范、規(guī)范和精品3個等級并將其作為KH-KELM的輸出，通過專家打分法獲得18個英語教學質(zhì)量評價二級指標數(shù)據(jù)并將其作為KH-KELM的輸入，建立KH-KELM的英語教學質(zhì)量評價模型。與KELM和SVM相比較，KH-KELM可以有效提高英語教學質(zhì)量評價的精度，為英語教學質(zhì)量評價提供新的方法和途徑。

關鍵詞：英語教學質(zhì)量;層次分析法;專家打分法;磷蝦群算法;評價指標體系;核極限學習機

中圖分類號：TP 391;G 523

文獻標志碼：A

文章編號：1007-757X（2020）11-0059-04

Abstract：In order to realize the English teaching quality evaluation and objectively reflect the English teaching quality level， an English teaching quality evaluation index system based on teachers quality， teaching attitude， teaching content， teaching method and teaching effect was constructed by using analytic hierarchy process. The English teaching quality level was divided into three grades：under-standard， standard and excellent， which were taken as the output of KH-KELM. The expert scoring method was used to obtain 18 English teaching quality evaluation second-level index data， which were taken as the input of KH-KELM， and the English teaching quality evaluation model of KH-KELM was established. Compared with KELM and SVM， KH-KELM can effectively improve the accuracy of English teaching quality evaluation and provide a new method and approach for English teaching quality evaluation.

Key words：English teaching quality;analytic hierarchy process;expert scoring method;Krill algorithm;evaluation index system;kernel extreme learning machine

0?引言

教學質(zhì)量是教育競爭力的核心內(nèi)容，高校教師教學質(zhì)量評價對提升教師教學能力和教學管理水平具有重要意義[1]。通過教學質(zhì)量評價，學生可以反饋教師教學情況，與此同時，教師可以反思教學效果，學校可以改進教學管理，有針對性地提出解決措施和辦法，從而提高教師的教學水平和教學質(zhì)量。目前高校教學質(zhì)量評價的方法主要有模糊綜合評價法[2]、層次分析法[3]、灰色關聯(lián)分析法[4]和神經(jīng)網(wǎng)絡法[5]等，這些方法取得了一定效果，然而存在隨機性和主觀性的缺點，導致無法準確評價教學質(zhì)量。為提高高校英語教學質(zhì)量評價的準確度，提出一種基于層次分析法（Analytic Hierarchy Process，AHP）和磷蝦群算法（Krill Herd，KH）改進核極限學習機（Kernel Extreme Learning Machine，KELM）的英語教學質(zhì)量評價方法。為了實現(xiàn)英語教學質(zhì)量評價，運用AHP構建出包含5個一級評價指標的英語教學質(zhì)量評價指標體系。……