Mice, rats, and humans have two types of estrogen receptors, estrogen receptor-␣ (ER␣) and estrogen receptor-␤ (ER␤). Estrogen receptor-␣ gene-disrupted (ER␣-disrupted) mice bear two nonfunctional copies of the ER␣ gene. This mutation blocks the synthesis of full-length ER␣, renders the animals infertile, and inhibits the induction of female sexual behaviors by estradiol and progesterone. It is likely that many of the processes contributing to the regulation of sexual receptivity by estradiol and progesterone are compromised in ER␣-disrupted mice. However, given the importance of progesterone in the regulation of sexual receptivity and given the importance of progestin receptors (PRs) in mediating the responses of females to progesterone, we investigated the effects of ER␣ disruption on the induction of PRs by estradiol in the forebrain.We hypothesized that estradiol would induce PRs in wildtype mice but not in ER␣-disrupted mice. Ovariectomized wildtype and ER␣-disrupted mice were implanted with either estradiol-filled capsules or empty capsules for 5 d, after which their brains were processed for the immunocytochemical detection of PR. Estradiol increased the number of PRimmunoreactive cells in both wild-type and ER␣-disrupted mice. The residual responsiveness of ER␣-disrupted mice to estradiol could be accounted for by an ER␤-dependent mechanism or another as yet unidentified estrogen receptor; however, because ER␣-immunoreactivity and PCR product representing the 3Ј end of ER␣ mRNA were found in at least one PR-containing region of the ER␣-disrupted mice, an ER␣ splice variant may also mediate the induction of PR-immunoreactivity in ER␣-disrupted mice.

Instructor Talk—noncontent language used by instructors in classrooms—is a recently defined and promising variable for better understanding classroom dynamics. Having previously characterized the Instructor Talk framework within the context of a single course, we present here our results surrounding the applicability of the Instructor Talk framework to noncontent language used by instructors in novel course contexts. We analyzed Instructor Talk in eight additional biology courses in their entirety and in 61 biology courses using an emergent sampling strategy. We observed widespread use of Instructor Talk with variation in the amount and category type used. The vast majority of Instructor Talk could be characterized using the originally published Instructor Talk framework, suggesting the robustness of this framework. Additionally, a new form of Instructor Talk—Negatively Phrased Instructor Talk, language that may discourage students or distract from the learning process—was detected in these novel course contexts. Finally, the emergent sampling strategy described here may allow investigation of Instructor Talk in even larger numbers of courses across institutions and disciplines. Given its widespread use, potential influence on students in learning environments, and ability to be sampled, Instructor Talk may be a key variable to consider in future research on teaching and learning in higher education.

Active-learning pedagogies have been repeatedly demonstrated to produce superior learning gains with large effect sizes compared with lecture-based pedagogies. Shifting large numbers of college science, technology, engineering, and mathematics (STEM) faculty to include any active learning in their teaching may retain and more effectively educate far more students than having a few faculty completely transform their teaching, but the extent to which STEM faculty are changing their teaching methods is unclear. Here, we describe the development and application of the machine-learning-derived algorithm Decibel Analysis for Research in Teaching (DART), which can analyze thousands of hours of STEM course audio recordings quickly, with minimal costs, and without need for human observers. DART analyzes the volume and variance of classroom recordings to predict the quantity of time spent on single voice (e.g., lecture), multiple voice (e.g., pair discussion), and no voice (e.g., clicker question thinking) activities. Applying DART to 1,486 recordings of class sessions from 67 courses, a total of 1,720 h of audio, revealed varied patterns of lecture (single voice) and nonlecture activity (multiple and no voice) use. We also found that there was significantly more use of multiple and no voice strategies in courses for STEM majors compared with courses for non-STEM majors, indicating that DART can be used to compare teaching strategies in different types of courses. Therefore, DART has the potential to systematically inventory the presence of active learning with ∼90% accuracy across thousands of courses in diverse settings with minimal effort.active learning | evidence-based teaching | science education | lecture | assessment C urrent college STEM (science, technology, engineering, and mathematics) teaching in the United States continues to be lecture-based and is relatively ineffective in promoting learning (1, 2). Undergraduate instructors continue to struggle to engage, effectively teach, and retain postsecondary students, both generally and particularly among women and students of color (3, 4). Federal analyses suggest that a 10% increase in retention of undergraduate STEM students could address anticipated STEM workforce shortfalls (5). Replacing the standard lecture format with more active teaching strategies has been shown to increase

A collaborative professional development program that engaged nearly 90% of faculty in a biology department in more than 40 hours of training on scientific teaching was instituted. Participating instructors integrated active learning in their courses, as shown through a variety of methods, and reported positive effects on teaching and departmental community.

Activation of steroid hormone receptors by steroid hormones alters both the physiology and behavior of animals. Steroid hormone receptors (e.g., progestin receptors) can also be activated in the absence of steroid hormones by pharmacological treatment with neurotransmitters or neuropeptides. However, it is not known if progesterone-independent activation of brain progestin receptors occurs under natural, physiological, conditions. We report that increases in reproductive behavior and brain immediate early gene expression in female rats induced by mating stimuli can be blocked by prior treatment with progesterone antagonists in the absence of circulating progesterone. This suggests that progestin receptors are activated in a progesterone-independent manner by a physiologically relevant stimulus in female rats, thus implicating a novel pathway by which mating stimuli and other environmental influences could activate steroid receptors to influence neuronal response and behavior.