MétaCan
Menu
Back to cohort
Record W2884039406 · doi:10.5539/hes.v8n3p49

Integrating Drone Technology with GPS Data Collection to Enhance Forestry Students Interactive Hands-On Field Experiences

2018· article· en· W2884039406 on OpenAlexvenueno aff
Daniel Unger, I‐Kuai Hung, Yanli Zhang, David Kulhavy

Bibliographic record

VenueHigher Education Studies · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGlobal Positioning SystemUnit (ring theory)Geographic coordinate systemGeographyMobile deviceGeographic information systemBachelorField (mathematics)CompassPoint (geometry)Computer scienceMathematics educationCartographyPsychologyMathematicsWorld Wide WebArchaeologyTelecommunications

Abstract

fetched live from OpenAlex

Undergraduate students pursuing a Bachelor of Science in Forestry (BSF) at Stephen F. Austin State University (SFA) within the Arthur Temple College of Forestry and Agriculture (ATCOFA) attend an intensive 6-week hands-on instruction in applied field methods. The second week of field station is focused on land measurement activities to introduce students to practical, hands-on, and technology based ways to survey forest boundaries. On Monday of the second week students are introduced to the concepts of how to use a handheld compass to navigate from point to point, use a consumer-grade handheld Global Positioning System (GPS) unit for collecting the geographic coordinates of given locations, use a GPS unit to calculate the area of a forest opening, use a GPS unit to walk and record a forest hiking trail, and evaluate the accuracy of their GPS derived locations via a Root Mean Square Error (RMSE) analysis. RMSE analysis between a students collected geographic coordinates and the instructors collected geographic coordinates indicated that the students were sufficient in correctly recording the geographic coordinates of point, line, and polygon features identified in the field. Grades on the student submitted reports summarizing Monday’s activities resulted in 33 of 56 students (59.0%) receiving a high A, 14 of 56 students (25.0%) receiving a low A, and 9 of 56 students (16.0%) receiving a high B indicating that the interactive hands-on nature of ATCOFA’s field station is effective at providing students with real-world applications whereby they will be ready to make a difference the day after graduation. Interactive drone imagery and video integrated into the daily activities in the field to enhance a student’s understanding of their specific objectives provided the students in the field with a bird’s eye perspective of the landscape to aid their understanding and planning of the field tasks assigned. In conclusion, employers can have confidence that when hiring recent BSF graduates from ATCOFA that the students have been introduced to geospatial technologies within a proven one-on-one instruction methodology designed to increase cognitive retention and can traverse from location to location accurately and record the geographic coordinates of earth surface features correctly.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.532
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.071
GPT teacher head0.410
Teacher spread0.339 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueHigher Education StudiesSame topicDiverse Educational Innovations StudiesFrench-language works237,207