Skip to main content. Search Close Search. You are currently using guest access Log in. A manually graded Moodle question type, where the student records a short audio response to answer the question asked.

This question type is like the standard essay question type, but instead of writing some text, students have a recording widget where they can record some audio in future, we plan to also add video recording.

We have essentially taken the existing parts and distilled them into a specific question type for the ease and convenience of teachers designing quiz questions and for the students taking them.

Like the standard essay question type, it still requires human grading. This question type has two behaviours: deferred feedback, for use in formal Moodle Quiz tests where a tutor would mark the students' recordings; and a new self-rating behaviour, where students mark themselves.

The self-rating behaviour is used essentially whenever the behaviour is interactive or immediate. We have assumed two use-cases: 1 the student listens to a 'model' audio clip and then records their attempt to follow it.

They compare the two clips, and then rate their mimicry. Or 2 the student attempts to pronounce a written sentence verbally, and the feedback contains a model pronunciation clip, allowing the student to then compare the clips and self-rate their accuracy.

We hope that we could look at giving Essay a self-rating behaviour next, which could be used in a similar embedded fashion as an alternative to Pattern Matching sentences.

Although if you're thinking about that area already, you might find Gordon Bateson's essay auto-grade plugin of interest. Potential privacy issues You should consider the fact that under GDPR, a recording of a user's voice is personally identifiable data it is arguably also biometric data.

Such 'Special category data' requires extra protection. One of the main critics of operationalism in social science argues that "the original goal was to eliminate the subjective mentalistic concepts that had dominated earlier psychological theory and to replace them with a more operationally meaningful account of human behavior.

But, as in economics, the supporters ultimately ended up "turning operationalism inside out". The above discussion links operationalization to measurement of concepts.

Many scholars have worked to operationalize concepts like job satisfaction , prejudice, anger etc. Scale and index construction are forms of operationalization.

There is not one perfect way to operationalize. For example, in the United States the concept distance driven would be operationalized as miles, whereas kilometers would be used in Europe.

Operationalization is part of the empirical research process. Both job satisfaction and job turnover need to be measured.

The concepts and their relationship are important — operationalization occurs within a larger framework of concepts. When there is a large empirical research question or purpose the conceptual framework that organizes the response to the question must be operationalized before the data collection can begin.

If a scholar constructs a questionnaire based on a conceptual framework, they have operationalized the framework. Most serious empirical research should involve operationalization that is transparent and linked to a conceptual framework.

To use an oversimplified example, the hypothesis Job satisfaction reduces job turnover is one way to connect or frame two concepts — job satisfaction and job turnover.

The process of moving from the idea job satisfaction to the set of questionnaire items that form a job satisfaction scale is operationalization.

For example, it is possible to measure job satisfaction using only two simple questions: 1 "All in all, I am satisfied with my job"; 2 "In general, I like my job.

Operationalization uses a different logic when testing a formal quantitative hypothesis and testing working hypothesis qualitative.

For formal hypotheses the concepts are represented empirically or operationalized as numeric variables and tested using inferential statistics.

Working hypotheses particularly in the social and administrative sciences , on the other hand, are tested through evidence collection and the assessment of the evidence.

The researcher asks - Is the evidence sufficient to 'support' the working hypothesis? Formal operationalization would specify the kinds of evidence needed to support the hypothesis as well as evidence which would "fail" to support it.

He identifies six sources of evidence 1 documentation; 2 archival records; 3 interviews ; 4 direct observations; 5 participant observation and 6 physical or cultural artifacts.

In the field of public administration, Shields and Tajalli have identified five kinds of conceptual frameworks working hypothesis , descriptive categories, practical ideal type, operations research, and formal hypothesis.

They explain and illustrate how each of these conceptual frameworks can be operationalized. They also show how to make conceptualization and operationalization more concrete by demonstrating how to form conceptual framework tables that are tied to the literature and operationalization tables that lay out the specifics of how to operationalize the conceptual framework measure the concepts.

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