Drs. Chris Schatschneider and Sara Hart, at the Department of Psychology and the Florida Center for Reading Research at the Florida State University, are recruiting a postdoctoral researcher to work with them on a NIH-funded project, called “LDbase”.
 
This postdoctoral position on the LDbase project is an opportunity to help create a repository of datasets related to academic achievement available to all researchers. One role on this project is to create a series of pooled datasets through the use of measurement invariance modeling using R and to make this code available to anyone who wants it. Another role is to publish manuscripts from these datasets. Another role will be to help create data management and data analysis resources for the broader academic community (e.g., data entry best practice guide, data analysis workshop slides). So if you’re looking for a job where you’ll get a lot of experience in measurement modeling, publishing manuscripts, as well as supporting educational and developmental science researchers in data sharing – then this job is for you!
 
We are hoping to recruit an individual is comfortable with advanced statistical procedures such as measurement modeling. Experience with data created by educational/learning disabilities researchers is a plus. Start date is tentatively set for August 9, 2021, but we are open to an early start date. Salary is set at the NIH-levels and benefits are set by our university, but we are able to add further support with generous travel and training opportunities, and a collegial and jovial work environment.
 
You can apply for this job by going to www.hr.fsu.edu, clicking on “job opportunities”, and searching for job id “48641”. Applicants will be asked to provide their CV, letter of interest, and names and contact information for three individuals for whom letters of recommendation could be solicited (with names and contact info to be submitted as directed in the Letters of Reference Section). We will be taking applications until the position is filled, so apply quickly! Questions can be emailed or tweeted to Chris (schatschneider@psy.fsu.edu, @schotz) or Sara (hart@psy.fsu.edu, @saraannhart).

Lab graduate student is now DR. Rasheda Haughbrook! Rasheda rocked her final (zoom) defense! She will be starting her new job in August, as an Assistant Professor of Teaching in the Department of Psychology at Florida State University! We are so proud of her, and are happy we don't have to say a full good-bye!

​Call for a Special Series in Learning Disability Quarterly on Registered Reports
 
This special series will focus on introducing the learning disability research community to a new way to publish, the registered report. Unlike regular empirical articles, registered reports go through peer review before the study is conducted or results of the research are known.  Authors submit their introduction, methods, analysis plans, and pilot data if applicable, as a “stage-1” manuscript. This manuscript then goes through peer review, with reviewers evaluating and making recommendations for study plans and authors responding. This process continues until the Editor rejects or grants “in-principle acceptance” to the stage-1 manuscript. If the stage-1 manuscript receives an in-principle acceptance, the authors then pre-register their approved study plans and start the study.
 
After completion of the study, the authors write up and submit a “stage-2” manuscript, which is the complete manuscript that adheres to APA formatting and LDQ Author Guidelines. At this stage, reviewers, the journal editor, and the guest editors review the completed manuscript to evaluate whether the pre-approved protocol was followed and conclusions are sound. If the plan was followed and results discussed appropriately, final acceptance is granted.
 
What makes registered reports different from regular publications is that the system of pre-review and pre-approval based on methodological quality:

1. Allows reviewers to provide constructive feedback proactively, before the study is conducted, which can be incorporated by the authors to improve the study.
2. Prevents reviewers and editors from deciding whether a publication merits publication based on (significant or interesting) findings, or forcing post-hoc changes to the analyses.
3. Removes the incentive for authors to engage in questionable research practices to attain statistically significant findings.

 
For this special series, our goal is to show the learning disability community that a range of research methodologies lend themselves to registered reports. Therefore, we are especially interested in publishing manuscripts that reflect a range of methodologies. We welcome submissions that propose using group experimental and quasi-experimental designs, single-case designs, correlational designs, qualitative methods, descriptive methods, individual differences methods, meta-analytical methods, secondary data analysis, replications, and other empirical methodologies appropriate for addressing research questions relevant to students with and at risk for learning disabilities. Proposed research studies must focus on empirically examining research questions with direct relevance for the education and outcomes of students with and/or demonstrably at risk for learning disabilities.
 
More information concerning registered reports, including workflow and checklists for investigators, is available here. As registered reports are likely new for many special education researchers, we welcome questions concerning process or fit (see below for e-mail addresses).
 
Now Accepting Extended Abstracts
We invite interested researchers to submit extended abstracts of planned stage-1 manuscripts. For consideration, please email your extended abstract submission* to Bryan Cook at bc3qu@virginia.edu. You will receive a confirmation of receipt. We will invite approximately five stage-1 manuscripts for the special series based on quality of proposed methods and contribution to a methodologically diverse set of studies for the special series.
 
Timeline
Abstracts should be submitted by February 15, 2020, with decisions on abstracts anticipated by March 1, 2020. If invited to contribute to the special series, stage-1 manuscript (consisting of a complete Introduction and prospective Method) will be submitted for peer review by June 1, 2020. It is expected that stage-1 review will be completed on or before October 15, 2020. If granted in-principle acceptance, full stage-2 manuscripts, reporting the completed study, will be submitted for review by August 15, 2021. We anticipate final decisions on stage-2 manuscripts by November 15, 2021.
 
* To allow the guest editors to evaluate and invite selected stage-1 manuscripts for the special series, we ask that interested researchers initially submit an extended abstract that provides the following details. We anticipate that extended abstracts will be one to two pages in length. Note that, depending on the research design, some of these categories may need to be modified. Our intent is for authors to provide us with a meaningful overview of the proposed study.
- Title 
- Study rationale/background
- Research questions (specify relevance for students with and/or at risk for learning disabilities)
- Primary research design/method
- Sample description
- Independent variable
- Measures and key outcomes 
- Data analytic strategy
- Feasibility of recruiting sample and conducting study within the timeframe of the special issue.
 
Feel free to contact us if you have questions:
Bryan Cook: bc3qu@virginia.edu
Bill Therrien: wjt2c@virginia.edu
Sara Hart: shart@fcrr.org
 

 

​http://ldbase.org/

​Drs. Chris Schatschneider and Sara Hart, at the Department of Psychology and the Florida Center for Reading Research at the Florida State University, are recruiting a postdoctoral researcher to work with them on a new NIH-funded project, called “LDbase” (LDbase.org).
 
This postdoctoral position on the LDbase project is an opportunity to help create a repository of datasets related to academic achievement available to all researchers. One role on this project is to create a series of pooled datasets through the use of measurement invariance modeling using R and to make this code available to anyone who wants it. Another role is to publish manuscripts from these datasets. Another role will be to help create data management and data analysis resources for the broader academic community (e.g., data entry best practice guide, data analysis workshop slides). This job also provides an opportunity to teach one class per year (during fall or spring). So if you’re looking for a job where you’ll get a lot of experience in measurement modeling, publishing manuscripts, as well as getting a course prepped – then this job is for you!
 
Candidates for this position must not be current students or staff at Florida State University. We are hoping to recruit an individual with a background in measurement modeling. Experience with data created by educational/learning disabilities researchers is a plus. Start date is tentatively set for August 8, 2019, but we are open to an early start date. Salary is set at the NIH-levels and benefits are set by our university, but we are able to add further support with generous travel and training opportunities, and a collegial and jovial work environment.
 
You can apply for this job by going to www.hr.fsu.edu, clicking on “job opportunities”, and searching for job id “44985”. Applicants will be asked to provide their CV, letter of interest, and names and contact information for three individuals for whom letters of recommendation could be solicited (with names and contact info to be submitted as directed in the Letters of Reference Section). We will be taking applications until the position is filled, so apply quickly! Questions can be emailed or tweeted to Chris (schatschneider@psy.fsu.edu, @schotz) or Sara (hart@psy.fsu.edu, @saraannhart).
 

By Keno Catabay: 

With such a wide pool of talented trainees in every academic concentration and in every  discipline at Florida State University, the following sentence may seem strange: You should consider adding a library and information science student to your application pool. Considering that I am an academic librarian-in-training, I will admit that I am a little biased. However, there is a concise methodology at work here.
In the fall semester of 2017, I was invited to join the Florida Learning Disability Research Center (FLDRC) under Dr. Sara Hart. On top of a project that studies the reading and math co-development in a diverse sample of twins, Sara is also in charge of the Engagement Core of the Center as well.
 
You may be asking: What is an Engagement Core? Well, here is a quick rundown…

• Serves as the central point of dissemination and translation of publications, research updates, and news.
• Serves as the private hub for scholarly communication within a research grant.
• Depending on the needs of faculty, develops innovative and efficient ways to share resources and research across multiple projects.
• Develops ways to track and train new researchers.

 

1. Knowledge of federal information policies.

 
A core course of the Master’s of Science in Information (MSI) program here at FSU is LIS 5411 – or information policy, which focuses on policy issues within the US government related to intellectual property, accessibility, privacy, service, and equity. Chances are, an MSI student has also taken advanced levels of this course as well.
 
At the FLDRC, I was able to give a webinar on the policies of federally-funded grants in regards to open data policy. If you are a researcher, there is a good chance that you are funded by some sort of grant. Adding someone from the library and information science world—even at the trainee level—can be helpful to your research process. MSI students can analyze and assess the quality of your data and assure that it is up to federal standards.  
 

        2. Emerging technologies and software that can aid in the research process.  

The library world is changing. The days of simple card catalogs and dial-up internet are long gone. In the past two decades, information technology and computer science has seen a boom like no other. In academia, library systems are pushing to get to the forefront of this encounter. Librarians are now learning how to code in a variety of languages—such as python, R, and SQL—and conducting workshops on how they can aid in research for all disciplines. On the technology side, FSU Libraries has successfully used 3D modeling and 3D printing as a supplement to several research projects by faculty.
 

       3. Knowledge on how to increase citation impact and providing metric reports.  

One of the core initiatives of academic librarians that work in digital research, digital scholarship, and academic publication is increasing the citation impact of publications, discovering ways for your research to reach a wider audience. Adding an MSI student into your project is a low-cost way to potentially boost the amount of times your research is cited by other scholars or on social media.
 

       4. Jack-of-all-trades academics, who may also be familiar with your field.  
​
Librarians are notorious for ending up in their field “accidentally.” Many MSI students are older, have work experience under their belt, and/or hold multiple degrees. You truly do not know the scope of an MSI student until you sit down with them for an interview. It is not uncommon for an MSI student to hold a J.D. or even a Ph.D.—somewhere along the line, they probably decided that their passion was in information access the entire time.
 
Doing research in STEM? Consider hiring an MSI student with a background in biology, computer science, or physics – there are more than you think. Attempting to recreate a dig site into a 3D model? Consider hiring an MSI student who has a degree in archaeology, anthropology, or classics. Attempting to digitize the works of a 20th century Beat writer? The MSI program is saturated with seasoned humanities students.
 
Not only are MSI students equipped to add library services and techniques to your research endeavors, but if you find a good match, they are likely to be familiar with your area of work as well.