How we learn and why we don't : student survival guide using the cognitive profile inventory /

Bibliografiske detaljer
Hovedforfatter:	Krause, Lois Breur
Format:	Bog
Sprog:	English
Udgivet:	Ohio : Cengage learning, 2008.
Udgivelse:	4th ed.
Fag:	Learning. Cognitive learning. Learning ability.
Classic Catalogue:	View this record in Classic Catalogue

Lignende værker

Essentials of learning : the new cognitive learning for students of education /
af: Travers, Robert Morris William, 1913-

How the special needs brain learns /
af: Sousa, David A.
Udgivet: (2001)

How the special needs brain learns /
af: Sousa, David A.
Udgivet: (2007)

Enjoying What We Don't Have
af: McGowan

Real-time mastitis detection in livestock using deep learning and machine learning leveraging edge devices
af: Ghosh, Kawshik Kumar, et al.
Udgivet: (2023)

Yoga posture recognition using the deep learning process
af: Islam, Abidul, et al.
Udgivet: (2023)

What every teacher should know about learning, memory, and the brain /
af: Tileston, Donna Walker
Udgivet: (2004)

Classification of peripheral blood cell images using deep learning
af: Aadi, Oyshik Ahmed, et al.
Udgivet: (2024)

Learning theories for teachers /
af: Bigge, Morris L.
Udgivet: (1982)

An efficient deep learning approach to detect skin Cancer
af: Islam, Ashfaqul, et al.
Udgivet: (2022)

Prostate cancer detection using deep learning neural network with transfer learning approach
af: Badhon, Ariful Islam Mahmud, et al.
Udgivet: (2022)

Classifying insect pests from image data using deep learning
af: Mohsin, Md. Raiyan Bin, et al.
Udgivet: (2022)

Sentiment analysis on Bangladesh airlines review data using machine learning
af: Hasib, Khan Md.
Udgivet: (2022)

A modern technique to detect potholes by Computer Vision and Deep Learning
af: Saif, Muntasir Mahmud, et al.
Udgivet: (2023)

Damaged road detection using Image Processing and Deep Learning
af: Swadesh, Shimran Mahbub, et al.
Udgivet: (2022)

Classification and Explanation of Different Internet of Things (IoT) Network Attacks using Machine Learning, Deep Learning and XAI
af: Tasnim, Anika, et al.
Udgivet: (2022)

Child learning, intelligence, and personality : principles of a behavioral interaction approach /
af: Staats, Arthur W.
Udgivet: (1971)

A comparative analysis of deep learning and hybrid models to diagnose multi-class skin cancer
af: Nawrin, Ishrat Nur, et al.
Udgivet: (2023)

How people learn : brain, mind, experience, and school /
Udgivet: (2000)

Classification of Bangla regional languages and recognition of artificial Bangla speech using deep learning
af: Hossain, Prommy Sultana
Udgivet: (2022)

An efficient deep learning approach to detect citrus leaves disease
af: Emon, Shaharear Hossain, et al.
Udgivet: (2024)

Enhancing underwater object detection through water artifact removal and using ensemble transfer learning
af: Saikat, Nayem Hossain, et al.
Udgivet: (2024)

Prediction and detection in change of cognitive load for VIP’s by a machine learning approach
af: Rahman, Fahim, et al.
Udgivet: (2021)

Corn leaf disease detection using deep convolution neural network
af: Rabbi, Rawhatur, et al.
Udgivet: (2023)

A texture based industrial fault diagnosis model using Gammatone Filter Bank and transfer learning
af: Morshed, Atique, et al.
Udgivet: (2021)

How the brain learns /
af: Sousa, David A.
Udgivet: (2006)

Deep learning based arrhythmia classification on low-cost and low-compute MCU
af: Zishan, Md Abu Obaida, et al.
Udgivet: (2023)

A deep learning approach towards soft biometrics attributes prediction using CNN
af: Kibria, Maharab, et al.
Udgivet: (2022)

Document template identification and data extraction using machine learning and deep learning approach
af: Roy, Kaushik, et al.
Udgivet: (2024)

Recall-Net: A CNN-based Model for Four-class Classification of Alzheimer’s Disease
af: Hasan, M. M. Kamrul, et al.
Udgivet: (2022)

Bang-lish sentiment classification using deep learning
af: Saleheen, Abrar, et al.
Udgivet: (2023)

DeepWPD: A deep learning based wavelet packet decomposition to remove Moiré pattern from screen capture images.
af: Khan, Ibrahim
Udgivet: (2023)

An efficient deep learning approach to detect skin cancer using image data
af: Chowdhury, Yaser Al Rahman, et al.
Udgivet: (2023)

RetinalNet-500: a newly developed CNN model for eye disease detection
af: Toki, Sadikul Alim, et al.
Udgivet: (2023)

E-learning software in the context of Bangladesh : proposal for an interactive model according to bloom's texonomy
af: Raihan, Ariful Hoque, et al.
Udgivet: (2010)

Implementation of machine learning to estimate the air pollutants such as Carbon dioxide, methane, nitrous oxide and total greenhouse gas emissions in Bangladesh
af: Biswas, Sunanda, et al.
Udgivet: (2022)

A secured federated learning system leveraging confidence score to identify retinal disease
af: Eshan, M Sakib Osman, et al.
Udgivet: (2023)

Why Don't American Cities Burn?
af: Katz

Classification of respiratory diseases and COVID-19 from respiratory and cough sound using deep learning techniques
af: Ahasan, Md. Mubtasim, et al.
Udgivet: (2022)

An interpretable transformer based approach to classify Malaria from blood cell images
af: Islam, Mehafuza, et al.
Udgivet: (2023)