LTI Tool Use
Last updated
Last updated
The mart_general.lti_tool keeps track of use of LTI tools in the learning environment.
mart_general
The following visualization shows the construction of this data mart defined in the repository. More information on the repository and diagram can be found on
udp_course_offering_id
INTEGER
The UDP ID for the Course offering associated with the LTI tool.
lms_course_offering_id
STRING
The LMS ID for the Course offering associated with the LTI tool.
sis_course_offering_id
STRING
The SIS ID for the Course offering associated with the LTI tool.
udp_person_id
INTEGER
The UDP ID for the person who used the LTI tool.
lms_person_id
STRING
The LMS ID for the person who used the LTI tool.
sis_person_id
STRING
The SIS ID for the person who used the LTI tool.
role
STRING
The role of the person who used the LTI tool, i.e. Learner or Instructor.
academic_term_name
STRING
The name of the academic term, i.e. Fall 2020.
academic_term_start_date
DATE
The start date for the academic term.
academic_organization_array
ARRAY<STRING>
An array of the name of the academic organization(s).
academic_organization_display
STRING
An array of the name of the academic organization(s) written as a comma-separated string.
course_offering_title
STRING
The title of the Course offering associated with the LTI tool, i.e. Linear Algebra.
course_offering_start_date
DATE
The start date of the Course offering associated with the LTI tool.
course_offering_subject
STRING
The subject of the Course offering associated with the LTI tool, i.e. MATH
course_offering_number
STRING
The number of the Course offering associated with the LTI tool, i.e. 310.
course_offering_code
STRING
The code of the Course offering associated with the LTI tool, i.e. MATH 310.
num_students
INTEGER
The number of students enrolled in the Course offering associated with the LTI tool.
udp_course_section_id
INTEGER
The UDP ID of the Course section associated with the LTI tool.
lms_course_section_id
STRING
The LMS ID of the Course section associated with the LTI tool.
sis_course_section_id
STRING
The SIS ID of the Course section associated with the LTI tool.
instructor_name_array
ARRAY<STRING>
An array of the instructors’ names for the Course offering associated with the LTI tool.
instructor_lms_id_array
ARRAY<STRING>
An array of the instructors’ LMS IDs for the Course offering associated with the LTI tool.
instructor_display
STRING
The array of the instructors’ names for the Course offering associated with the LTI tool written as a string.
instructor_email_address_array
ARRAY<STRING>
An array of the instructors' email addresses for the Course offering
instructor_email_address_display
STRING
An array of the instructors' email addresses for the Course offering written as a comma-separated string
event_time
DATETIME
The time that the LTI tool was launched.
event_day
DATE
The date that the LTI tool was launched.
event_hour
INTEGER
The hour that the LTI tool was launched.
launch_app_url
STRING
The URL of the application launched.
launch_app_domain
STRING
The domain of the application launched.
launch_app_name
STRING
The name of the application launched.
tool_name
STRING
The name of the LTI tool.
is_lti_tool
BOOLEAN
A boolean indicating if the tool launched is a LTI tool.
is_redirect_tool
BOOLEAN
A boolean indicating if the tool launched is a redirect tool.
The num_students field defines the number of enrolled students in a Course offering. This number is found from the course_section_enrollment table in UDP’s context store, which keeps track of enrollments in course sections. We count the number of enrollments with a role of ‘Student’ or ‘Observer’ and a role status that is not ‘Dropped’, ‘Withdrawn’, or ‘Not-enrolled’.
The field event_time defines the time the event associated with when the tool launch took place from the LMS. This field is derived from the UDP’s event store.
This is the fully resolved URL of the launched tool. We pull this from the object.extensions chunk of the JSON Caliper event. Usually the URL comes from the url key of this chunk, but depending on the tool, it can also come from the domain key. We coalesce these values with preference to the url key if it exists.
The launch_app_domain is extracted from the domain key of the object.extensions chunk of the JSON Caliper event. Usually, this will be a subset of the full url value. Often, the launch_app_domain field can be useful to group events together in the event that a single tool has multiple resolved URL values.
The launch_app_name is extracted from the asset_name field of the object.extensions chunk of the JSON Caliper event. This is often a more human-readable name of the tool that is helpful for front-end reporting and visualization.
Unizin has compiled a list of common tools that are used across the consortium. The tool_name field does not exist natively in the Caliper event, but instead is a mapping table we crafted to further help with grouping and organizing LTI tool launches. Both the launch_app_name and launch_app_url fields are used for this mapping to tool_name, with the preference being launch_app_url. Currently 940 URLs and 313 app name values are mapped to tool_name values; if a value shows up that is not in the managed mapping table, a value of ‘unknown tool’ is returned.
This field alongside launch_app_name is intended to be the most useful for visualization and reporting. The launch_app_name field comes directly from the Caliper event, and the tool_name field comes from Unizin’s managed list.
We separate LTI tool launches from Redirect tool launches. Two areas of the event are critical to determine whether the event in scope is an LTI tool launch or a redirect launch:
The domain key from object.extensions.[‘com.instructure.canvas’]
The url key from object.extensions.[‘com.instructure.canvas’]
is_lti_tool
Is not null or blank
is_redirect_tool
Is null or blank
As a starting point for visualization for this data mart, Unizin has created a Tableau template workbook available for download here:
Unizin does not provide active, production support for the visualizations, filters, and aggregations in the Tableau workbooks. They are intended to be used as-is, but modifications are welcome! However, we will provide support related to connecting to source data and any issues with the Bigquery -> Tableau workflow.
Once downloaded, ownership of the workbook is transferred to the user. Unizin does not host the workbook on a Tableau Server instance.
The following fields are used as filters in the Tableau Workbook:
Academic Organization - The academic department name.
Launch App Name - The list of tools that are used.
Course Offering Code - The course code of the course offering.
Academic Term - The academic term of the course; the default selection is the current term.
These filters are in scope for all visuals in the dashboard.
These metric cards provides a quick summary of tool usage across courses. It highlights the total number of tool launches, unique users, distinct tools used, and courses where tools were launched. This shows the overall adoption and engagement with LTI tools at the institution.
The tool usage patterns show when and how often LTI tools are used, helping to identify peak usage times and trends over time. It offers insights into usage patterns across days and hours, supporting decisions around tool support and optimization.
Courses are grouped by the number of unique LTI tools they use, helping reveal patterns in tool adoption. The distribution also highlights engagement levels across courses and shows how widely tools are being integrated into the learning experience.
Students are categorized based on the number of unique LTI tools they have interacted with. The chart displays the percentage of students in each group, helping to understand engagement depth and how broadly tools are being utilized by the student population.
Tool usage breakdown across the week shows how the LTI tool usage is distributed across each day of the week, This helps identify which days see higher engagement, supporting scheduling decisions and resource planning.
Tools usage at different times displays tool usage by hour across all days, helping identify peak hours of engagement.
Top 15 most frequent tools used per day highlights the most commonly used LTI tools for each day of the week. This view helps identify which tools drive the most daily engagement and supports decisions around tool prioritization.
This visualization shows the top 15 most tools that are used the most in different courses. It helps to see which tools are most popular and commonly used by students in their courses.
This chart tracks the total number of tool launches each day for different tools, showing how usage changes over time. This helps to identify patterns and fluctuations in tool engagement during the course.
This table displays usage patterns, such as the average number of launches per course or student, for different tools. It helps provide insights into overall engagement of tools at the institution.
Academic data overview displays overall tool usage metrics for courses, as well as contextual data about the course, such as department, course title, and instructors. This overview provides insights into how LTI tools are utilized across various courses and departments, helping to understand engagement and tool adoption in academic settings.
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The default data connection in the workbook is to Unizin's synthetic data. After downloading the workbook, the first step will be to transfer the connection to your own production UDP data. Here is a to help with this process; Tableau also has a for replacing data sources. For any issues connecting to source data, please contact support@unizin.org.
