Special topics in counseling, therapy and school, psychology. Students may obtain a course, description from the department office or website.
- Teacher: Justin Henderson
Category: Couns, Therapy and School Pych
Lewis & Clark Moodle
Search results: 1941
Special topics in counseling, therapy and school, psychology. Students may obtain a course, description from the department office or website.
- Teacher: Justin Henderson
Category: Couns, Therapy and School Pych
Special topics in counseling, therapy and school
psychology. Students may obtain a course
description from the department office or website.
psychology. Students may obtain a course
description from the department office or website.
- Teacher: Cort Dorn-Medeiros
Category: Graduate School Fall 2024
Special topics in counseling, therapy and school
psychology. Students may obtain a course
description from the department office or website.
psychology. Students may obtain a course
description from the department office or website.
- Teacher: Meg Jeske
Category: Couns, Therapy and School Pych
Special topics in counseling, therapy and school, psychology. Students may obtain a course, description from the department office or website.
- Teacher: Meg Jeske
Category: Graduate School Summer 2022
This course covers the descriptive and inferential, statistics practitioners use in their professions., There is an overview of quantitative research, designs with the focus on understanding and, application of data analysis and interpretation., Coverage includes basic descriptive and, inferential statistics, appropriate interpretation, of statistical results, and real-world, presentation of data. Note: Taught in spring, semester only. Students who wish to pursue the, thesis-option M.S. program are required to take, this course if conducting a quantitative thesis, project.
- Teacher: Emily Usher
Category: Couns, Therapy and School Pych
This Moodle page is for CTSP to access Placement Office-related information.
ctspplacement@lclark.edu
503-768-6094
- Teacher: Educational Technology Administrator
- Teacher: Angelina Almukhametova
- Teacher: Julio Appling
- Teacher: Kristine Bella
- Teacher: Janet Bixby
- Teacher: Wonyoung Cho
- Teacher: Jeffrey Christensen
- Teacher: Alexia Deleon
- Teacher: Cort Dorn-Medeiros
- Teacher: Nori Gruber
- Teacher: Pilar Hernandez-Wolfe
- Teacher: Bernette Jenkins-Pleas
- Teacher: Stella Kerl-Mcclain
- Teacher: Ayshia Moua
- Teacher: Juleen Norling
- Teacher: Patricia Palczewska
- Teacher: CTSP Placement
- Teacher: Counseling Psychology
- Teacher: Amy Rees
- Teacher: Educational Technology
- Teacher: Jessica Thomas
- Teacher: Chelsey Torgerson
Category: Couns, Therapy and School Pych
Internship in a community setting. Participants, engage in counseling and related professional, activities under supervision. Students write, reports, prepare case histories, and submit work, samples for supervisory review.
- Teacher: Stella Kerl-Mcclain
Category: Graduate School Fall 2019
Academic and experiential bridge between classroom, theory and real-world application in the domain of, data science. Students enrolled in this course, will work eight to 10 hours per week in small, teams to solve problems and extract value from, data. The problems and data sets will vary by year, and course offering, but will universally provide, opportunities to students to frame research, questions, manage and clean data, execute, analyses, and communicate results.
- Teacher: Greta Binford
- Teacher: Ethan Davis
- Teacher: Jeremy McWilliams
- Teacher: Amelia Pruiett
Category: Data Science
Academic and experiential bridge between classroom
theory and real-world application in the domain of
data science. Students enrolled in this course
will work eight to 10 hours per week in small
teams to solve problems and extract value from
data. The problems and data sets will vary by year
and course offering, but will universally provide
opportunities to students to frame research
questions, manage and clean data, execute
analyses, and communicate results.
theory and real-world application in the domain of
data science. Students enrolled in this course
will work eight to 10 hours per week in small
teams to solve problems and extract value from
data. The problems and data sets will vary by year
and course offering, but will universally provide
opportunities to students to frame research
questions, manage and clean data, execute
analyses, and communicate results.
- Teacher: Greta Binford
- Teacher: Ethan Davis
- Teacher: Jeremy McWilliams
- Teacher: Emily O'Sullivan
Category: Data Science