I have gotten into a bit of a rut with my evaluations, and language sampling is an area where I have broad freedom to create my own best practices. That’s why in 2018, I’m setting myself up for change with a clear goal to perform better language analysis!
I’m a little embarrassed that I need to write this goal for myself. I was a good graduate student — and it wasn’t that long ago! I learned the value of language sampling and the power a language sample has to anchor a solid evaluation. But when I look at my recent work, I know I could do better. And, even more importantly, I wouldn’t need to take more time or be any more complicated than what I’m already doing!
Here are three steps I’ve laid out for myself to make sure this is a New Years resolution I’ll keep:
- The first step to moving forward is to acknowledge there is a problem. And I have found plenty of evidence that this problem is bigger than just me (phew?). Pavenko et al’s recent review of a nationwide survey on the issue reported that only two-thirds of the school-based SLP respondents had even analyzed a language sample in the given school year, and of those who had, most were self-designing their protocol, transcribing in real time, and using conversation and picture description as collection tasks regardless of client age.Instead of being embarrassed that I have to set this goal for myself, I am going to be a part of the solution, improving my own behavior and setting a higher standard for myself and my colleagues!
- No need to reinvent the wheel! It’s worth my time to review what’s out there and see what tools others are using. In a brief review, I identified three tools I’m excited about exploring:
- SALT (Systematic Analysis of Language Transcripts) is a software program I already own. I found an update to make it run on my newer computer, and have already reinstalled it. I have, in the past, found it less valuable for my older students. Ready to explore.
- CLAN (Computerized Language Analysis) is free language analysis software. It seems powerful and exciting, but I’m worried that it might involve a lot of coding, possibly proving too complicated for me to make my own. Intrigued.
- DYMOND (Dynamic Measure of Oral Narrative Discourse) is a standardized dynamic assessment of oral narratives for school-age children. This free download is a protocol based on this recent study. And by using it, I can contribute data towards national norms. That feels good!
- Talk about my goal with others. Not only does it force me to outwardly commit, but it keeps me accountable. As I have talked with my colleagues about this resolution, I’ve been reminded that lots of SLPs love language sampling! It is a great water cooler topic.
So here’s my goal for myself as it stands:
By June 2018, Kira will improve her language sampling skills by a) reviewing recent journal articles to compile a list of valuable things she’s already doing, b) learning about and trialing at least 2 different new-to-her tools, c) conducting and reporting on language samples with at least 6 different students, d) sharing her questions and learning with at least two colleagues.
May 2018 be a year of carefully executed progress on well-written goals, mixed in with surprising discoveries and unpredicted success.