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Three strategies for assessment in autonomous language learning Joan Jamieson, Northern Arizona University, USA & Carol A. Chapelle, Iowa State University,

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Presentation on theme: "Three strategies for assessment in autonomous language learning Joan Jamieson, Northern Arizona University, USA & Carol A. Chapelle, Iowa State University,"— Presentation transcript:

1 Three strategies for assessment in autonomous language learning Joan Jamieson, Northern Arizona University, USA & Carol A. Chapelle, Iowa State University, USA

2 Three Strategies  Adaptivity  Feedback  Self-assessment

3 An Adaptive Strategy  Learner would benefit from more than one form of material  Computer should select appropriate form based on responses to questions

4 Overview of LEA Interest and Ability Finder Beginning Reading Beginning Listening Beginning Writing Intermediate Reading Intermediate Listening Intermediate Writing Advanced Reading Advanced Listening Advanced Writing Results & Recommendations Results & Recommendations Results & Recommendations

5 The Interest Survey  Select test form  Select recommendations

6 Items on Interest Survey

7 Example Strategies

8 A Feedback Strategy  Learner benefits from total scores  Learner might benefit more from part scores

9 Example Computing Total Score

10 Part Scores Reflect Subskills  Tests are often made up of subskills  Each item can be coded according to subskill  Scores for subskills can be computed by including codes

11 Table of Specifications

12 Tags for LEO Tests TAGWhat the TAG means Llistening LINlistening for information LIDlistening for ideas Ggrammar G1grammar point 1 G2grammar point 2 G3grammar point 3 Sspeaking Vvocabulary Rreading Ppronunciation P1pronunciation point 1 P2pronunciation point 2

13 Tags in Script for Grammar Section

14 Using Tags with System Variables  “score” yields percentage correct  score (tag) yields percentage correct for any items with a given “tag”  score (G2) yields percentage correct of 2 nd point of grammar—expressions for suggesting

15 Combining Tags and System Variables score (L | G | V | S | P | R) n/m1= “rawscore(LIN) / tqw(LIN)” n/m2= “rawscore(LID) / tqw(LID)” n/m3= “rawscore(G1) / tqw(G1)” n/m4= “rawscore(G2) / tqw(G2)” n/m5= “rawscore(G3) / tqw(G3)”

16 Mock-up of Progress Report Screen Progress Report LEO 3 Test Learner’s name: Score: score (L | G | V | S | P | R) Language areaNumber correct/number of items Listening for informationn/m1 Listening for ideasn/m2 Grammar (point1*)n/m3 Grammar (point2*)n/m4 Grammar (point3*)n/m5

17 Screen Shot of Progress Report

18 Using Tags to Report Scores

19 A Self-Assessment Strategy  Learner may benefit by comparing his/her perspective of performance with score  Computer can collect self-confidence data along with performance data

20 Example of Self-Confidence Item Was your answer correct? How sure are you? Click a circle below. Completely Not sure at all sure

21 Superimposed Self-Assessment Item Was your answer correct? How sure are you? Click in a circle for each answer. 1. 2. 3. Completely Not sure sure at all

22 Computing Average Confidence (Tarone and Yule, 1989) Circle clicked 54 3 2 1 total average confidence correct answers 205 3 2 0 294.52 incorrect answers 00 4 5 2 112.00 (20*5)+(5*4)+(3*3)+(2*2)+(0*1)/29 = 4.52 (4*3)+(5*2)+(2*0)/11 = 2.00 Tarone, E., & Yule, G. (1989). Focus on the language learner. Oxford, UK: Oxford University Press.

23 Computing Self-Monitoring Index  Derived by subtracting self-confidence rating on incorrect items from self-confidence rating on correct items: 4.52 – 2.00 = 2.52  Index ranges in value from 4 to - 4  Messages could be provided instead of numbers

24 Self-Assessment Superimposed onto Progress Report Self-Assessment: You seem to be aware of your own ability. When you gave the correct answer, you were very sure you were correct. When you gave the wrong answer, you were not too sure you were correct.

25 Implementing Self-Assessment  Tag self-assessment items  Save value of “rawscore (SA)” separately for correct and incorrect items: IF ANSWER = 1 THEN SAOK = SAOK + rawscore (SA) IF ANSWER = 0 THEN SANO = SANO + rawscore (SA)

26 Calculating Average Scores  AVGSAOK = SAOK / # CORRECT ITEMS  AVGSANO = SANO / # INCORRECT ITEMS  MONITORING INDEX = AVGSAOK-AVGSANO

27 Example of Computing Self- Assessment Scores

28 Three Strategies for Individualizing Assessment  Adapting level, content, and recommendations based on learner’s responses  Additional feedback in the form of diagnostic scores  Self-assessment to heighten learner’s metacognitive awareness

29 Three strategies for assessment in autonomous language learning Joan Jamieson, Northern Arizona University, USA & Carol A. Chapelle, Iowa State University, USA


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