Archive for March, 2017

How Do You Know if Your Students Are Engaged?

Check out Shannon Seidel’s work on active learning in the new Division of Natural Sciences newsletter: Synapse. Want more? Click here!

Discover your class!: Dr. Joseph Ross Explains his view on DART


As Owens’ manuscript suggests, this brings opportunity for institution-wide, automated analysis of teaching practices without having to have person-time in the classroom or watching (and coding) course videos. This is a game-changer. Read the manuscript for more potential benefits.

The reason I was so excited about DART this morning is because I pride myself on incorporating active learning in my courses at Fresno State. Plus (the BIG plus), I have years of lecture capture recordings that I could be analyzing RIGHT NOW! So, before getting ready for work this morning, I threw a few of my .mp4 file exports from ExplainEverything at DART.

Thus, a key benefit is those of us with stockpiles of audio can get straight to analysis. Today.

Further, with audio recording devices being dead cheap (ranging from dedicated digital audio recorders to cell phones, laptops, tablets…), everybody can (and should!) start analyzing their teaching style using this technique. Today. Except…

If you would like to read more, click here

Congratulations Genesis on UCSF!!

Screen Shot 2016-03-10 at 1.30.28 PM

Congratulations to SFSU and SEPAL SPIKE alumna, Genesis Vasconez, in her acceptance to the UCSF Masters Entry Program in

Loud and Clear with the DART App

Inside Higher Education writes its insight on the new DART App, used to measure the extent to which professors use active learning in their classrooms.

For more info, click here

New PNAS Publication on an Algorithm that Uses Sound to Identify Teaching Practices in College Classrooms!

Detecting active learning in college classrooms 

Researchers designed an algorithm that uses sound to identify teaching practices in college classrooms. Previous studies show that classes with active learning, when students learn through talking and problem solving, result in higher learning gains and student retention than lecture-only classes. Hundreds of millions of dollars have been invested to shift science, technology, engineering, and math (STEM) college courses from the common lecture-based teaching style to more active learning. Kimberly Tanner and colleagues designed Decibel Analysis for Research in Teaching (DART), a machine-learning algorithm that rapidly analyzes classroom audio recordings, to quantify the frequency of different teaching practices in a classroom. For 1,486 recordings from 67 college courses across 21 community colleges and universities, DART distinguished the amount of classroom time spent with no voices or thinking/writing time, one voice or lecture/question-and-answer time, and multiple voices or discussion time. DART identified teaching styles with an approximately 90% accuracy rate and worked well in both small and large classes. The amount of time spent on active learning activities—both no voices and multiple voices activities—was higher for courses for STEM majors than courses for non-STEM majors, and 88% of courses analyzed here used active learning in at least half of class sessions. Given its efficiency, DART makes regular, systematic analyses of the use of active learning in classrooms possible for individual instructors, departments, institutions, and researchers, according to the authors.DART Trace

For more information, click here

Congratulations Analisa: Moving forward in the CSU Student Research Competition!!

thumb_Analisa Brown_1024

Congratulations on winning the SFSU level of the CSU Student Research Competition in the Area of Education and being chosen to compete at the CSU level for your biology research efforts investigating the experiences of Black students in the SFSU Biology department!!