WebQuest Assessment Tool

WebQuest Assessment Tool

So the next CALL project I’m tackling for the class I’m taking this semester is to develop a WebQuest for language learners. To kick off this project we’re going to be talking about some of the CALL assessment tools we plan to use. So, to get things started, first, let me start with a brief description of what I’m planning for this WebQuest.

I would like to work with the topic of food to explore the adjectives and descriptions that can be found on menus. I would do this WebQuest with intermediate-level Japanese students studying English as a foreign language, namely 3^rd year junior high school students (Ages 14-15).  I plan to have students work collaboratively in groups of three for this WebQuest, where they will look at various restaurant websites to assemble a personal corpus of food-related descriptive language. While I’m not yet certain what CALL technology I want them to use to present their final product (and therefore don’t yet know how it will be assessed), so far I have decided on two documents that these groups will be required to complete.

In an attempt to give my student a “paperless classroom” experience, I would like to try to do as much of the basic assignments using only the computer. For this reason, I think I would give each student group a Google account that the groups “techie” (one of the student roles) could access and edit their assignments in. These Google docs and spreadsheets would be shared with me so that I could also digitally provide immediate feedback to the groups as needed.

The first document that student groups will work on is the “Word Chart” Google Doc, which will look like this when students first access it:

This document contains a three-column table that students will complete in two stages; the first two columns of the table are to be completed at the beginning of the WebQuest (and without the help of any dictionaries), while the third and final column will be completed after the WebQuest has been completed. This activity was inspired by Egbert’s (2007) discussion of using self-assessment tools in language learning, in which he states:

“At the beginning of a lesson, learners using a pretest-posttest model can note what they know at the beginning of a lesson and what they want to know at the end. At the end of the unit or lesson, learners can look back at the pretest and note what they now know and whether or not they have learned what they wanted to learn” (p. 252).

Though my proposed word document self-assessment task deviates from the typical know-want to know-learned (KWL) activities that she was describing here, I believe that the self-assessment tool I’ve created here will help learners take note of their progress in the following ways:

• By first listing the adjectives they know in Japanese (their L1), my students can become aware of all the different words they use in their native language to describe food.
• Students at this level will likely not be able to translate all of the words they listed in their L1 into their L2 for the second column, which will show them the gaps in their vocabulary knowledge.
• Students will be allowed to copy items from their second (pretest) column into their third (posttest) column before adding the terms they learned during the WebQuest; the third column should therefore be longer than the second, helping students visualize the gains they’ve made in their English vocabulary knowledge

Additionally, by having students type their word lists into a digital document rather than have them write it on paper, they can take advantage of the program’s spell-check feature. This gives them extra confidence when writing words from memory into their second column as well as when inputting newly encountered words into their final column.

Because this is a self-assessment tool, its main purpose is to help students reflect on their progress and understanding; it’s therefore my intention to grade this portion of the WebQuest only for its completion. However, since I don’t have all of the assessment tools ready at this point, I’m not sure how much weight this part of the WebQuest will have on the students’ final grades.

The second document I want my students to work on is a corpus of food-related description words (sweet, crispy, rich, grilled, steamed) including the sample sentences that they found on the various online menus I’ll provide for them. Though the act of gathering vocabulary words and sample sentences seems like a simple scavenger hunt activity, I believe this step is important for language learners in this WebQuest because it arms them with the L2 knowledge base they need in order to progress to the more “transformative learning” tasks that “real” WebQuests aim for (March, 2004, p. 42).

I will give the groups an initial file with a list of English words to search for, and it will be up to them to find these words on the various websites. They are to take note of which nouns these words can be used to describe (as in, I might say “a creamy milkshake,” but I wouldn’t say “a creamy tomato”) and provide the sample sentence in which they found that descriptor being used. This was inspired by the fact that in Japanese the verb “yaku” is often translated into English as a number of different things: grill, bake, cook, etc. My 3^rd year students also study reduced relative clauses in the latter half of their textbooks, so I thought this WebQuest might be a relevant way for them to practice that knowledge.

This corpus that the groups assemble will also be submitted to their Google Drive in the form of a spreadsheet. Tentatively the blank file I’ll give them will look something like this:

This will likely have much more influence on the group’s overall grade, but again, this corpus is merely going to be a tool for their ultimate project in which students will use these adjectives and descriptions to assemble their own list of appetizing daily specials for a fictitious restaurant of their choosing. Again, because this is merely a tool to help students gain some familiarity and confidence with the material, I would likely focus on completion and accuracy (no spelling errors, no irrelevant examples, etc.) for grading this portion of the WebQuest.

This is, as of right now, my plan to incorporate technology into the assessment of my WebQuest. As always, comments, criticisms, and suggestions are always welcome!

References:

Egbert, J. (2007). Classroom practice: Practical classroom assessment. In Egbert, J., & Hanson-Smith, E. (Eds.), CALL environments: Research, practice, and critical issues (pp. 242-257). Alexandria, VA: Teachers of English to Speakers of Other Languages.

March, T. (2004). The learning power of WebQuests. Educational Leadership, 61(4), pp. 42-47.