As a psychology professor, I regularly teach research methods courses. Over a two-course sequence, I teach my students various approaches to empirical psychological research. This culminates in a semester-long project in which students formulate a hypothesis, design a study, collect and analyze data, and communicate the results.

One issue that repeatedly comes up is finding measures for students to use in their projects. In psychology studies – particularly those implemented in undergraduate methods’ courses – a measure is often a questionnaire or other structured set of questions that can be completed by participants and scored quantitatively. The questions used to measure a given construct – for example, depression, anxiety or extraversion – are usually (ideally) well–established and the product of a rigorous validation process. As such, it’s important that students locate the most appropriate measures for their study, and finding such measures is an important skill.

Historically, locating a measure usually involved wading through search results and associated papers, trying to figure out what is most used and well-validated. This was a time-consuming process that was often well outside the scope of an undergraduate methods course.

With scite Assistant, it's much easier. For example, the query "What are the most commonly-used measures of depression?" immediately yields a number of options, two of which I usually point students to if depression is one of their variables of interest: the CES-D and the BDI.

Assistant is also helpful identifying critiques of well-established measures. In response to the query, "Is the Rosenberg Self-Esteem Scale valid?", it provides important context and points to criticisms of the measure.

I often suggest that students use Assistant in this way (asking about validity) to point out the unsettled state of the science on even the most widely-used psychometric instruments.

Finally, there are some areas where the number of measures is so numerous, it’s difficult to identify which is the most appropriate for a given research question. For example, religiosity (the extent to which a person is religious) can be assessed by a wide variety of questionnaires (so many that a 500+ page book compiling all of them was published). Asking Assistant "What is a good measure of religiosity related to health?" produces the following response:

This is close to what I would have recommended if a student had asked me directly. Of course, I chose these examples because I can vouch for Assistant’s responses (I know they're good answers!), but the real power comes in when students – and professors, researchers, etc., for that matter – use it to learn about measures in areas with which they are relatively unfamiliar.

If you'd like a walkthrough on how you can use scite in the classroom book some time here: https://scite.ai/request-a-demo.