[br][table][br][br][tr][br][td]Eigenvalue[/td][br][td]固有値[/td][br][td]고유값[/td][br][td]特征值[/td][br][/tr][br][tr][br][td]Eigenvector[/td][br][td]固有ベクトル[/td][br][td]고유벡터[/td][br][td]特征向量[/td][br][/tr][br][tr][br][td]Matrix[/td][br][td]行列[/td][br][td]행렬[/td][br][td]矩阵[/td][br][/tr][br][tr][br][td]Characteristic polynomial[/td][br][td]特性多項式[/td][br][td]특성 다항식[/td][br][td]特征多项式[/td][br][/tr][br][tr][br][td]Diagonalization of matrices[/td][br][td]行列の対角化[/td][br][td]행렬의 대각화[/td][br][td]矩阵对角化[/td][br][/tr][br][tr][br][td]Linear algebra[/td][br][td]線形代数[/td][br][td]선형 대수[/td][br][td]线性代数[/td][br][/tr][br][tr][br][td]Linear transformations[/td][br][td]線形変換[/td][br][td]선형 변환[/td][br][td]线性变换[/td][br][/tr][br][tr][br][td]Eigenvalues and Eigenvectors applet[/td][br][td]固有値と固有ベクトルのアプレット[/td][br][td]고유값 및 고유벡터 애플릿[/td][br][td]特征值和特征向量小程序[/td][br][/tr][br][tr][br][td]Stability of systems[/td][br][td]システムの安定性[/td][br][td]시스템의 안정성[/td][br][td]系统稳定性[/td][br][/tr][br][tr][br][td]Transformation matrix[/td][br][td]変換行列[/td][br][td]변환 행렬[/td][br][td]变换矩阵[/td][br][/tr][br][tr][br][td]Invariant properties[/td][br][td]不変性質[/td][br][td]불변 성질[/td][br][td]不变性质[/td][br][/tr][br][tr][br][td]Positive eigenvalue[/td][br][td]正の固有値[/td][br][td]양의 고유값[/td][br][td]正特征值[/td][br][/tr][br][tr][br][td]Negative eigenvalue[/td][br][td]負の固有値[/td][br][td]음의 고유값[/td][br][td]负特征值[/td][br][/tr][br][tr][br][td]Zero eigenvalue[/td][br][td]ゼロ固有値[/td][br][td]제로 고유값[/td][br][td]零特征值[/td][br][/tr][br][/table][br]

[table][br][tr][br][td][b]Factual Questions[/b][br]1. What is the definition of an eigenvalue?[br][br]2. How do you find the eigenvalues of the matrix A = [[2, 1], [1, 2]]?[br][br]3. What is an eigenvector and how is it related to its corresponding eigenvalue?[br][br]4. Calculate an eigenvector corresponding to one of the eigenvalues of the matrix A = [[3, -2], [1, 0]].[br][br]5. Explain the process of determining the eigenvalues and eigenvectors for a 3x3 matrix.[br][/td][br][br][td][b]Conceptual Questions[/b][br]1. Explain the significance of eigenvalues and eigenvectors in linear algebra.[br][br]2. Discuss the physical interpretation of eigenvalues and eigenvectors.[br][br]3. How does the characteristic polynomial relate to finding eigenvalues?[br][br]4. Explain the role of eigenvalues and eigenvectors in the diagonalization of matrices.[br][br]5. Compare the computational methods for finding eigenvalues and eigenvectors of large matrices.[br][/td][br][br][td][b]Debatable Questions[/b][br]1. Is the concept of eigenvalues and eigenvectors more abstract than other concepts in linear algebra? Why or why not?[br][br]2. Debate the practical applications of eigenvalues and eigenvectors in real-world problems.[br][br]3. Can understanding eigenvalues and eigenvectors significantly enhance problem-solving skills in engineering and physics?[br][br]4. Discuss the statement: "The study of eigenvalues and eigenvectors is essential for a deep understanding of linear transformations."[br][br]5. Evaluate the impact of computational software on learning and understanding the concepts of eigenvalues and eigenvectors.[br][/td][br][/tr][br][/table][br][br]

Scenario: The Enigma of Eigenvectors[br][br]Background:[br]In the mystical realm of Linear Algebraica, there lies an ancient puzzle known as the Enigma of Eigenvectors. This puzzle is said to hold the key to unlocking the secrets of linear transformations across the land.[br][br]Objective:[br]As a promising young mathematician, you are determined to solve the Enigma using the "Eigenvalues and Eigenvectors" applet, which visually demonstrates the effects of linear transformations on vectors.[br][br]Investigation Steps:[br][br]1. Understanding the Transformation:[br] - Study the transformation matrix provided in the applet and visualize how it affects vectors in the plane.[br][br]2. Finding the Eigenvalues:[br] - Use the applet to calculate the eigenvalues of the matrix, which represent the scaling factors in the transformation.[br][br]3. Discovering the Eigenvectors:[br] - Adjust the applet to find the eigenvectors, which are the vectors that do not change direction under the transformation.[br][br]4. Interpreting the Results:[br] - Analyze how the eigenvalues and eigenvectors describe the transformation and its invariant properties.[br][br]Questions for Investigation:[br][br]1. Discovery Question:[br] - How do the eigenvalues and eigenvectors help in understanding the stability of the system represented by the matrix?[br][br]2. The Power of Eigenvalues:[br] - What does it mean when an eigenvalue is positive, negative, or zero in the context of transformations?[br][br]3. Real-world Applications:[br] - How can the concept of eigenvalues and eigenvectors be applied in fields such as physics or engineering?[br][br]4. Reflection:[br] - Reflect on the importance of visual tools like this applet in grasping complex mathematical concepts.[br]