Which answer is NOT one of the four ways teachers can help students refocus on the text?

Allowing students to only make personal connections

Pose questions that require students to return to the text

All are text-dependent tasks except

Providing examples from their lives

Of the four types of feedback, which one is NOT useful?

Feedback about the self as a person (Fs)

Feedback about the processing of the task (FP)

Feedback about self-regulation (FR)

Making instructional decisions about what should happen next for the class as a whole

To provide as food or nourishment

Annoyed or upset at a situation

Primarily offered at the individual level

An error analysis sheet is for

Identifying and highlighting who are struggling

Accessing complex texts does NOT require

Students to do something after reading

Access Point 5 | Quizalize

GRADE 4 Module 6 Lesson 3. Interpret Remainders This PowerPoint file contains instructional aids for teachers who have purchased Into Math. It is intended to be projected to students and used in conjunction with the Student Edition and manipulatives as needed. These slides can be used to move the conversation forward in the classroom, but they should not serve as a replacement for student-centered, collaborative conversations in which students have the space they need to find an entry point, construct meaning, and build understanding. About the Slide Presentation Presenter View: Use the Presenter view to see notes while presenting. Customization: Add or delete content or notes to get the best learning experience for your classroom. 1 Problem of the Day. Which equations can be used to solve the following problem? Rita makes 40 bracelets and gives an equal number to 8 friends, including Veronica. Veronica gives 2 of the bracelets that she received to her sister. How many bracelets does Veronica have left? A. 40 – 8 = 32 32 ÷ 2 = 16 B. 40 ÷ 8 = 5 5 + 2 = 7 C. 8 + 2 = 10 40 ÷ 10 = 4 D. 40 ÷ 8 = 5 5 – 2 = 3 2 I Can. I Can solve a division problem and interpret the remainder in the context of the problem. 3 Spark Your Learning. Aiden is building solar toy cars in his science club. The cars collect and use energy from the sun for power. Aiden buys 18 wheels. Each car needs 4 wheels. How many cars can Aiden build? Show your thinking. 4 Turn and Talk. What is the remainder in this problem? What does the remainder mean? Professional Development note: Use the Professional Learning Cards to provide language routines that may help students access the meaning of the problem. 5 Build Understanding • Task 1 ACTIVITY. There are 57 students going to the science museum. Each van can take 5 students. How many vans are needed to take all the students? Use a visual model to show how the students are divided into groups of 5. 6 Turn and Talk. How can you use the whole-number quotient and remainder to answer these questions? How many vans will be full? How many students will ride in the van that is not full? Professional Development note: Use the Professional Learning Cards to provide language routines that may help students access the meaning of the problem. 7 Step It Out • Task 2 ACTIVITY.. Amanda has 73 inches of wire for a science experiment. She needs to cut all the wire into 8 identical pieces. How many inches long will each piece be? 8 Turn and Talk. Why is this problem a good situation to write the remainder as a fraction? Professional Development note: Use the Professional Learning Cards to provide language routines that may help students access the meaning of the problem. 9 Check Understanding. 1. Maya needs 44 batteries for smoke alarms. The batteries come in packs of 6. How many packs does Maya need to buy? For 44 ÷ 6, the whole-number quotient is ____ and the remainder is ____. Maya needs to buy ____ packs. Circle how you interpreted the remainder to solve the problem. 10 I Can Scale. 4 I can explain how to solve a division problem and interpret the remainder in the context of the problem. 3 I can solve a division problem and interpret the remainder in the context of the problem. 2 I can solve a division problem and identify the whole-number quotient and the remainder. 1 I can solve a division problem with a remainder. 11 Exit Ticket. Mr. Jenkins’ class is giving speeches during a 46-minute class. Each student will be able to talk for 4 minutes. How many students can give speeches? Justify your answer.

Mediul wireless transportă semnale electromagnetice care reprezintă cifre binare pentru comunicațiile de date care folosesc frecvențe radio sau de microunde. Ca și mediu de rețea, wireless nu este restricționat la conductori sau căi de acces, așa cum sunt mediile din fibră sau cupru. Mediul wireless asigură cele mai bune opțiuni de mobilitate dintre toate mediile. Astfel, numărul de echipamente wireless este în continuă creștere. Din aceste motive, wireless a devenit o opțiune pentru toate rețelele de domiciliu. Pe măsură ce opțiunile lățimii de bandă cresc, wireless crește în popularitate în rețelele companiilor. Figura evidențiază câteva simboluri cu privire la wireless. În orice caz, wireless-ul are câteva zone de preocupare precum: • Aria de acoperireTehnologiile de comunicare a datelor wireless funcționează bine în mediile deschise. În orice caz, unele materiale de construcție folosite în structuri și clădiri și terenul local vor limita aria de acoperire. • InterferențaWireless-ul este predispus la interferențe și poate fi întrerupt de echipamente obișnuite cum ar fi telefoane fără fir, unele tipuri de lumină fluorescentă, cuptoare cu microunde și alte comunicații wireless. • SecuritateaAcoperirea comunicației wireless nu necesită acces fizic la mediu. Așadar, echipamentele și utilizatorii care nu au autorizație pentru a accesa rețeaua pot obține accesul la transmisie. În consecință, securitatea rețelei este o componentă principală pentru administrarea rețelei wireless. Deși wireless-ul crește în popularite pentru conectivitatea calculatoarelor, fibra și cuprul sunt cele mai populare medii ale layer-ului fizic pentru dezvoltarea rețelelor. Tipuri de Mediu Wireless IEEE și standardele industriei de telecomunicații pentru comunicarea wireless a datelor acoperă atât layer-ului fizic, cât și layer-ul data link. Există patru standarde uzuale de comunicare a datelor care se aplică mediului wireless: • Standard IEEE 802.11Tehnologia WLAN (Wireless LAN), denumită și Wi-Fi, folosește un sistem nedeterminist sau controversat cu un proces de acces la mediu CSMA/CA (Carrier Sense Multiple Access/Collision Avoidance). • Standard IEEE 802.15Standardul WPAN (Wireless Personal Area Network), cunoscut și ca "Bluetooth", folosește un proces de împerechere a echipamentelor pentru a comunica pe distanțe cuprinse între 1 și 100 metri. • Standard IEEE 802.16Cunoscută de obicei ca WiMAX (Worldwide Interoperability for Microwave Access), folosește o topologie de tip point-to-multipoint pentru a furniza acces broadband de tip wireless. Figura evidențiază câteva diferențe ale mediilor wireless. Notă:Celelalte tehnologii wireless cum ar fi comunicațiile prin satelit și celulare pot asigura și ele conectivitatea rețelei de date. În orice caz, aceste tehnologii wireless depășesc scopul acestui capitol. În fiecare din exemplele de mai sus, specificațiile layer-ului fizic sunt aplicate zonelor care includ: • Codificarea semnalului radio sau de date • Frecvența sau puterea de transmisie • Recepția semnalului sau cerințele de decodificare • Construcția și design-ul antenei Notă:Wi-Fi este marcă înregistrată Wi-Fi Alliance. Wi-Fi este utilizat împreună cu produse certificate care aparțin echipamentelor din WLAN bazate pe standardele IEEE 802.11. LAN Wireless O implementare uzuală wireless a datelor este permiterea echipamentelor să se conecteze prin wireless la un LAN. În general, un LAN wireless necesită următoarele echipamente de rețea: • Puncte de Acces Wireless (AP)Concentrează semnalele wireless de la utilizatori și se conectează, de obicei printr-un cablu de cupru la infrastructura de rețea existentă bazată pe cupru, cum ar fi Ethernet. Routerele wireless din companiile mici sau de domiciliu integrează funcțiile unui router, switch și punct de acces într-un echipament, așa cum se arată în figură. • Plăcile de rețea wirelessAsigură capacitatea de comunicare wireless la fiecare host de rețea. Având în vedere că tehnologia s-a dezvoltat, a apărut un număr de standarde WLAN bazate pe Ethernet. Este necesară atenția atunci când se achiziționează echipamentele wireless pentru a asigura compatibilitatea și interoperabilitatea. Beneficiile tehnologiilor de comunicare a datelor wireless sunt evidente, în special conveniența ce reiese din mobilitatea hostului și reducerea costurilor necesare cablării. În orice caz, administratorii de rețea trebuie să dezvolte și să aplice politici de securitate și procese pentru a proteja LAN-urile wireless împotriva accesului neautorizat și a defecțiunilor. Standardele 802.11 Wi-Fi În ultimii ani au fost dezvoltate mai multe standarde 802.11. Standardele includ: • IEEE 802.11aFuncționează pe banda de frecvență de 5 GHz și oferă viteze de până la 54 Mb/s. Deoarece acest standard funcționează la frecvențe înalte, are o arie de acoperire mică și este mai puțin eficientă la penetrarea structurilor construcțiilor. Echipamentele care funcționează în cadrul acestui standard nu sunt interoperabile cu standardele 802.11b și 802.11g descrise mai jos. • IEEE 802.11bFuncționează pe banda de frecvență de 2.4 GHz și oferă viteze de până la 11 Mb/s. Echipamentele care implementează acest standard au o arie mai mare și pot pătrunde mai bine în structurile clădirilor decât echipamentele bazate pe 802.11a. • IEEE 802.11gFuncționează pe banda de frecvență de 2.4 GHz și oferă viteze de până la 54 Mb/s. Echipamentele care implementează acest standard funcționează la aceeași frecvență de radio și arie ca și 802.11b dar cu lățimea de bandă de la 802.11a • IEEE 802.11nFuncționează pe benzile de frecvență de 2.4 GHz sau 5 GHz. Rata așteptată a datelor este cuprinsă între 100 Mb/s și 600 Mb/s cu o distanță care poate ajunge până la 70 metri. Este compatibil cu echipamentele 802.11a/b/g. • IEEE 802.11acPoate funcționa simultan pe benzile de frecvență 2.4 GHz și 5.5 GHz și asigură rate de până la 450 Mb/s și 1.3 Gb/s (1300 Mb/s). Este compatibil cu echipamentele 802.11a/b/g/n. • IEEE 802.11adCunoscut și ca "WiGig". Folosește o soluție Wi-Fi pe trei benzi folosind 2.4 GHz, 5 GHz și 60 GHz și oferă viteze teoretice de până la 7 Gb/s. Figura evidențiază câteva din aceste diferențe.

New Trends in Agriculture Extension approaches Extension has been, and still is, under attack from a wide spectrum of politicians and economists over its cost and financing. As a result, Extension Systems have had to make changes, by restating the system’s mission, developing a new vision for the future, and formulating plans for the necessary transition to achieve the desired change. 1. Privatization of Agricultural Extension Service Privatization: Process of funding and delivering the extension services by private individual or organization is called Private Extension. Concept: Privatization of extension refers to services rendered in rural area & allied aspects of extension personnel working in private agencies or organization for which farmers are expected to pay a fee & it can be viewed as supplementary or alternative to public extension services (Sarvanan & Shivalinge 1980). Privatization approaches ➢ Share cropping system ➢ Village extension contract system ➢ Public extension through private delivery ➢ Service for vouchers Strengths of Private Extension System ➢ More demand - driven rather than supply – driven ➢ High quality of services in terms of satisfying information needs of clientele, trained manpower, sustained finances and resource allocation ➢ Provides for an information mix and choices available to farmers ➢ Enhanced efficiency of staff ➢ Assure continuous supply and quality agricultural products ➢ More effective because farmer can select an adviser who is the best able to help ➢ Healthy competition among service provider will lead to better quality and lower costs for service Weakness of Private Extension System ➢ Concentrate on area having favorable physical environment ➢ More face-to-face contacts (person oriented) ➢ Increased dependence of farmers and hence exploitation ➢ No education role ➢ Deprivation of small farmers ➢ Hamper the free flow of information 2. Cyber Extension or e-extension Concepts Cyber space: it is the imaginary or virtual space of computers connected with each other on Networks, across the Globe. Cyber extension: it means 'using the power of online networks, computer communications and digital interactive multimedia to facilitate dissemination of agriculture technology. Cyber Extension thus can be defined as the extension over cyber space. Important tools of cyber extension E-Mail, Telnet, File Transfer Protocol (FTP), Gopher, Archie and World Wide Web (WWW) Strengths of Cyber Extension ➢ Access to the astounding information and continuously available ➢ Information rich and instantaneously available of information ➢ Interactive communication ➢ The information is available from any point on the globe ➢ Communication is dynamic ➢ Cut steps from traditional process ➢ Save money, time and effort ➢ Multiplicity of purpose Issues and Concerns of Cyber Extension ➢ Lack of Reliable Telecom Infrastructure in Rural Areas ➢ Erratic or no Power Supply ➢ Lack of ICT Trained manpower (willing to serve) in Rural Areas ➢ Lack of content (locally relevant and in local languages) ➢ Lack of Information Services to Rural Clientele ➢ Low Purchasing power of the Rural communities ➢ Lack of Holistic Approaches ➢ Issues of Sustainability Application of cyber extension ➢ Village information shops Dr. M.S. SwaminathanResearch Foundation, Chennai ➢ Information villagers MANAGE in Ranga Reddy District in Andhra pradesh ➢ Gyandoot net initiative of District Dhar, Madhya Pradesh. ➢ Warna wired village of National Informatics Center (NIC) in Kolhapur- Sangli Districts of Maharashtra 3. Market-Led-Extension (MLE) Concepts Market: A congregation of prospective buyers & sellers with a common motive of trading a particular commodity. Extension: It is the spreading/reaching out to the mass Market-led-extension: Agriculture & economics coupled with extension is the perfect blend for reaching at the door steps of common man with the help of technology. Dimensions of market-led extension ➢ Marketing mix: A planned mix of the controllable elements of a product's marketing plan commonly termed as 4Ps: product, price, place, and promotion. These four elements are adjusted until the right combination is found that serves the needs of the product's customers, while generating optimum income. ➢ Marketing plan: A marketing plan is a comprehensive document that outlines a business and marketing efforts for the coming year. It describes business activities involved in accomplishing specific marketing objectives within a set time frame. A marketing plan also includes a description of the current marketing position of a business, a discussion of the target market and a description of the marketing mix that a business will use to achieve their marketing goals. ➢ Market Intelligence: It is the information relevant to a company’s markets, gathered and analyzed specifically for the purpose of accurate and confident decision making. Market intelligence includes the process of gathering data from the company’s external environment, whereas the business intelligence process is primarily based on internal recorded events – such as sales, shipments and purchases. ➢ Market oriented production ➢ Use of Technology Strengths of market-led extension ➢ SWOT analysis of the market ➢ Organization of Farmers’ Interest Groups (FIGs) ➢ Enhancing the interactive and communication skills of the farmers ➢ Establishing marketing and agro-processing linkages ➢ Advice on product planning ➢ Educating the farming community ➢ Direct marketing ➢ Acquiring complete market intelligence ➢ Publication of agricultural market information Production of video films of success stories ➢ Challenges to market-led extension ➢ Gigantic size of extension system ➢ Information technology Diverse conditions ➢ Market intelligence ➢ Reforms in agricultural extension system Government Initiatives ➢ Central warehousing Corporation-1965 ➢ MSP by Commission for Agricultural Cost and Price (CACP) ➢ Food Corporation of India ➢ Then some others as: Cotton Corporation of India (CCI), Jute Corporation of India (JCI), National Dairy Development Board (NDDB), Agriculture and Processed food Export Development Authority (APEDA) etc. 4. Farmer--Led-Extension (FLE) Farmer--led-extension is defined as 'the provision of training by farmers to farmers, often through the creation of a structure of farmer promoters and farmer trainers' (Scarborough et al., 1997). Philosophy and principles ➢ Farmers and local institutions (e.g. producer organizations or village leaders) should play a key role in selecting farmer-trainers and monitoring and evaluating them. This helps make the programmes more accountable to the community or groups that they serve. ➢ Farmer-trainers are ‘of the community’; they communicate in local languages and are more sensitive to local cultures, mannerisms, farming practices, and farmers’ needs. ➢ Farmer-trainers should be selected on the basis of their skills and interest in sharing information, not just on their farming expertise. ➢ Farmer-trainers need strong linkages with and support from development agents (whether government, non-government organization (NGO), or private), the people who train and backstop them. Farmer-trainers generally serve as a complement to existing extension systems, rather than being a substitute for them. ➢ Facilitating organizations and local institutions need to be proactive in ensuring that women as well as men become farmer-trainers. ➢ Simple and appropriate reference materials should be made available to the farmer trainers. Essential Elements of Farmer--led-extension ➢ The group ➢ The Field ➢ The Facilitator ➢ The curriculum ➢ Programme leader ➢ Financing Special features of Farmer--led-extension ➢ All learning is field based & it is primary venue for learning ➢ FLE group learning constantly over the experimentation period ➢ FLE promotes healthy decisions & quality decisions ➢ Farmers conduct their own field studies with comparisons or treatments ➢ Facilitates Farmer-to-Farmer communication ➢ Field staff serve as facilitators ➢ FLE is a unique way to educate farmers ➢ It is an effective platform for sharing of experiences and collectively solving agriculture related problems. 5. Expert system Expert system is an intelligent computer program that uses knowledge and inferences procedures to solve problems (Daniel Hunt, 1986). Objectives of developing expert system ➢ To enhance the performance of agricultural extension personnel and farmer ➢ To make farming more efficient and profitable ➢ To reduce the time required in solving the problems ➢ To maintain the expert system by continuously upgrading the database Advantages of expert system ➢ Solves critical problems by making logical deductions without taking much time ➢ It combines experimental and conventional knowledge with the reasoning skills of specialists ➢ To enhance the performance of average worker to the level of an expert Limitations of expert system ➢ Expensive computer program ➢ Mostly developed not in regional languages ➢ Requires AC power and internet connection all the time ➢ Complex software requires computer skilled personnel Modules of expert system in agriculture ➢ COMAX: Integrated crop management in cotton ➢ SOYEX: Soybean oil extraction expert system ➢ PLANT/ds: Diagnosis of soybean diseases ➢ MAIZE: Maize expert system for field crop management ➢ SEMAGI: Weed control decision making in sunflowers ➢ Rice Crop Doctor: Developed by National Institute of Agricultural Extension Management (MANAGE) Difference between conventional and expert system of extension Conventional Extension ➢ Universal approachability of same information is a problem ➢ Information is given whatever is available without considering needs and resources ➢ No Cost benefit analysis ➢ Information flow depends on availability of agent ➢ Require users to draw their own conclusion from facts Expert System of Extension ➢ Universal approachability of same information is possible ➢ Information is chosen based on their needs and resources ➢ Cost benefit analysis ➢ Information through Cyber Cafe at any place at any time ➢ Conclusion is drawn based on the decision given by the expert

Why and How Managers Plan Importance of planning The planing process Benefits of planning Planning and time management Types of PLans used by managers Long term and short term plans Strageic and tactical plans Operational plans Planning Tools and Techiqunes Forecasting Contrigency planning Scenario planning Benchmaking Use of staff planners Implementing Plans to Achive Results Goal setting Goal management Goal alignment Participation and involvement Planning Def: The process of setting objectives and determining how best to accomplish them Planning at Eaton Corporation “Making the hard decision before events force them upon you, an anticipating the future needs of the market before the demand asset itself Objectives and goals Identifity the specific results or desired outcomes that one intends to achieve Plan Def: A statement of action steps to be taken in order to accomplish the objectives (goals) Steps in the planning process: Define your objectives Determine where you stand vis-a-vis objectives Develpo premises reagrdsing future conditions Analyze alternatives and make a plan Implement the plan and evaluate results What are the benefits of planning Improves focus and flexibility Imporves action orteitation Imporves coordination and control Imporves time management Time Managment Personal time management tips Do say “no” to request that distract you form what you should be doing Dont get bogged down inn details that can be addressed later Do screen telephone calls, emails and meeting request Dont let drop in visitors, text messaging use up your time Do prioritize your important and urgent work Dont become calendar bound by letting other control your schedule Do follow priorities; do most important and urgent work first Some 77% of mangers in one survey said that digital age has increased th number of decisions they have to make 43% said there was less time available to make these decisions Types of plans used by Managers What is teh time horizon Long term vs Short term Long term Look three or more years into teh future Short term plans Typically cover one year or less However: the increasing environmental complexity and dynamism of recent years has severely tested the concept of “long-term” planning Plans are subject to frequent revisions Most executives would likely agree that these complexities adn uncertainties challenge how er actually go about planning and how far ahead we can really plan At the very least we can conclude that there is a lot less permanency to long term plans today and that tey are subject to frequent revision Managment reaeracher Eillot Jaques believes tha people vary in their capability to think with different time horizons Types of Plans used by Managers (3 of 5) Strategic plans Set broad, comprehensive and linger term action directions for teh entire organization or major division Vision Clarifies purpose of the organization and what it hopes to be on the future Typical plans Specify how the organizations resources are used to implement strategy Tactical plans in business often take the form of functional plans Functional plans Incidate how different component within the organiztion will help accompnlish the overall strategy Production plans Finacial plans Facilites Plans Logisitc plans Marketing plans Human Resource Plans Operation plans Describe short-term activities to implement strategic plans Policies: Are standing plans that communicate guidelines for decisions Ex: Policies on office romances: The media is quick to report when a top executive or public figures runs into trouble over an office affair. Are there ant policies on office romances? Employer polices on office raltioshiis vary. One survey find teh following: 24% prohibit relationships among employees in the same department 13% prohibit relationships among employees who have the smae supervisor 80% prohibit relationships between supervisors and subordinates 5% have no restrictions on office romances Procedures: Are rules that describe actions to be taken in specific situations Budgets: are single use plans that commit resources to projects or activities Zero based budgets: allocate resources as if each budget were brand new There is no guarantee that any past funding will be renwer. All propsales, old and new, must compete for available funds at teh start of each new budget cycle Forcasting Attempts to predict the future Qualitaive forecasting uses expert opinions Quantitative forecasting uses mathematical models and statiscal aanylsis of historical data dna surveys Contingency planning Identify alternative course of action to take when things go wrong Anticipate changing conditions Contain trigger points to indicate when to activate plan (or a specific course of action) Scenario planning A long term version of contingency planning Identifying alternative future scenarios Plans made for each future scenario Increases organizations flexibility and preparation for future shocks Benchmarking Use of external and internal comparisons to better evaluate current performance Adopting best practices: things people adn organization do that lead to superior performance Staff Planners Experts who assist in all steps of the planning process They help bring focus and expertise to a wide variety of planning tasks Important: Communication between staff planers landline managers is essential for teh success of teh planning process Goal Setting - Always set SMART goal The solution: Goal Aligment Between Team Leader and Team Member Jonintly plan: Set objectives, set standards, choose actions Individually acy: Perform tasks (member), provide support (leader) Jointly control: Review results, discuss implications, renew cycle x4 Collective effort and commitment Participatroy planning Includes in all planning steps that people who will be affected by the plans adn askedd to help implement them Unloacks motivational potential of goal setting Management by objective (MBO) promotes participation Participation increases understanding and acceptance of plan and commitment to success Participatory planning - Number of people involved in teh decision making process Amazon is intensely focused on what it does. It believes in creating tight single-threaded teams, also known as “2 pizza team.” Data and Decision Making What are some of the important competencies managers must have today? Delegate Marketing and technology Manager must have Technological competency Ability to understand new technologies and to use them to their best advantage Information competency Ability to locate, gather, organize and display information for decision-making and problem solving Analytical competency Ability to evaluate and analyze information to make actual decisions and solve real problems What is the difference between Data and Information Data Raw facts and observation Information Data made useful and meaningful for decision-making Important concepts Big data Exists in huge quantities and is difficult to process without sophisticated mathematical and analytical techniques Data production today Bernard Marr is an internationally best-selling author. He helps organizations improve their business performance, use data more intelligently Data mining The process of analyzing data to produce useful information for decision-makers Management Analytics The systematic evaluation and analysis of data to make informed decision Information drives management Bad Data Refers to information that can be erroneous, misleading, and without general formatting The challenge: Can er use the data that is available in the “Big Data” Needs to be valid Can not trust everything out there Being ethical Look at the trends Data is structured and unstructured Data BIg Data = Structured + Unstructured Information Drive Management decision making What are the characteristics of useful information Easy to access If its credible Accurate Characteristics of useful information: Timely High quality Complete Relevant Understandable What about bad data It's not credible Miss information If it is not structured/ organized Bias based on opinions Confusing If its updated Bad data Refers to information that can be erroneous miss What are some examples of Management information system Business intelligence -BI Information systems to extract and report data in organized ways that are useful to decision-makers Executive dashboards Visually update and display key performance metrics (or Key Performance Indicators -KPIs) and information on a real-time basis Information needs in organization External Environment Information exchanges with the external environment Gather intelligence information Provide public information Information needs within the organizations (internal Enviroement) Information exchange within the organization Facilitate decision making Facilitate problem-solving Managers as information processors Continually gather, share and receive information Now as much electronic as it is face-to-face Always on, always connected How many people telecommute at least once a week 70% of people globally work remotely at least once a week, Work at home after covid 19 our forecast Our best estimate it that 25-30% of the workforce will be working form home multiple days a week by the end of 2021 As of 2023, 12.7% of full time employees work from home, while 28.2% work a hybrid model Managers as problem solvers Problem-solving The process of identifying a discrepancy between actual and desired performance and taking action to resolve it Ishikawa Fishbone diagram To identify the cause of problems Decision A choice among possible alternative courses of action Performance threat Something is wrong or has the potential to go wrong Performance opportunity The situation offers the chance for a better future if the right steps are taken Problem-solving approaches or style - from textbook Problem avoiders Inactive in information gathering and solving problems Problem seekers Proactive in anticipation of problems and opportunities and taking appropriate action to gain an advantage Problem solvers Reactive in gathering information and solving problem Managers - can approach problems in a systematic or intuitive manner Systematic thinking approaches problem in rational, step-by-step and analytical fashion Intuitive thinking approaches problems in a flexible and spontaneous fashion Multidimensional thinking- applies both intuitive and systematic thinking Managers face structured and unstructured problems Structure problems Are ones that are familiar, straight forward, and clear with respect to information needs Program decisions apply solutions that are readily available from past experiences to solve structured problems Know how to solve them Familiar Know what we are dealing with Unstructured problems Are ones that are full of ambiguities and information deficiencies Nonprogrammed decisions apply a specific solution to meet the demands of a unique problem Commonly faced by higher-level management Crisis decision making A crisis involves an unexpected problem that can lead to disaster if not resolved quickly and appropriately Ruled for crisis management Figure out what is going on Remember that speed matters Remember that slow counts, too Respect the danger of the unfamiliar Value the skeptic Be ready to “fight fire with fire” Managers make decisions with various amounts of information Certain environment Offers complete information on possible action alternatives and their consequences Risk environment Lacks complete information but offers probabilities of the likely outcomes for possible action alternatives Uncertain environment Lacks so much information that it is difficult to assign probabilities to the likely outcomes of alternative Ex: Certain and uncertain environments: The worldwide Governance Indicators for over 200 countries, comparing distinct environments (Canada-Brazil) Step 1-Identify and define the problem Focuses on information gathering information processing and deliberation Decision objectives should be established What are some common mistakes in definding problems? Common mistakes in defining problems Defining the problem too broadly or too narrowly Focusing on symptoms instead of causes Choosing the wrong problem to deal with Step 2- Generate and Evaluate Alternative Courses of Action Potential solutions are formulated and more information is gathered, data are analyzed, the advantages and disadvantages of alternative solutions are identified Common mistakes: Abandoning the search for alternatives too quickly Step 3- Decide on a preferred course of Action Two different approaches Behavioural model leads to satisficing decisions Classical model les to optimising decisions Behavioural Model Rationality is bounded because: There are limits our thinks capacity Available information (incomplete) Time constraints Step 4-Implement the decision Involves taking action to make sure the solution decided upon becomes a reality Managers need to have the willingness and ability to implement action plans Problems: Lack of participation error should be avoided Step 5 - Evaluate Results Involves comparing actual and desired results The positive and negative consequences of the chosen course of action should be examined If actual results fall short desire results, the manager returns to earlier steps in the decision-making process At all steps, check ethical reasoning Ask these spotlight questions Utility Does teh decision satisfy all constituents or stakeholders Rights Does the description respect the rights and duties of everyone? Justice Is the decision consistent with the canons of justice Caring Is the decision consistent with my responsibilities to care? Issues in decision-making How do errors happen? Heuristics: are strategies for simplifying decision-making Availability Bias: Bases a decision on recent information or events Representativeness bias: Bases a decision on similarity to other situations Anchoring and Adjustment Bias: Bases a decision on incremental adjustment from a prior decision point Framing error: Tring to solve a problem in the context perceived, positive or negative Confirmation Error: Focusing on information that confirms a decision already made Escalating commitment: Continuing a course of action even though it is not working Creative Decision making Creativity is the generation of a novel idea or unique approach that solves a problem or crafts an opportunity Big C: Creativity occurs when extraordinary things are done by exceptional people Little C: Creativity occurs when average people come up with unique ways to deal with daily events and situations The three types of situational creativity drivers Chapter review What are objectives and goals? The specific results or desired outcomes What are the 5 characteristics of great (SMART) goals? Forecasting - Attempts Qualitative forecasting uses options Quantitative forecasting uses mathematical models and statistical analysis of historical data and surveys Scenarios-Oracle’s crystal ball combines qualitative and quantitative methods

Understanding the Connection Diagram of Fire Detection and Alarm System (Four Stations) Assessment 1. What are the key components of a fire detection and alarm system? a. Only smoke detectors b. Heat detectors and manual call points c. Control panels and power supply units d. Alarm sounders and batteries 2. Why is the synchronized response of alarm activation at all stations essential in a fire detection and alarm system? a. To confuse occupants b. For individual station evacuation c. Quick evacuation and response to emergencies d. Delay emergency response 3. How are the stations wired to the control panel in the connection diagram? a. Through a single circuit b. Via a complex network of cables c. Through a series of circuits d. Wirelessly 4. What happens if a detector at any station is triggered by smoke or heat in the connection diagram? a. It activates the alarm sounders at one station b. It sends a signal to the control panel for deactivation c. It triggers the alarm sounders at all four stations d. It has no effect on the system 5. In the wiring configuration, what role does a series circuit play in the system? a. Activates the alarm at one station only b. Triggers the alarm at all stations c. Prevents alarms from sounding d. Bypasses the control panel 6. Why are parallel circuits used in the fire detection and alarm system? a. To save on wiring costs b. To independently connect each station to the control panel c. To limit the number of alarm sounders d. To increase the chance of false alarms 7. What is critical for ensuring the proper functioning of the fire detection and alarm system? a. Irregular testing b. Absence of testing c. Regular testing and maintenance d. Testing only alarms 8. What does regular testing and maintenance help identify in the system? a. Issues with batteries and control panels b. The presence of smoke or heat in the environment c. The need for new detectors d. Alarm sounder malfunctions 9. Why is the connection diagram important in maintaining system integrity? a. To confuse users during emergencies b. To ensure the system malfunctions c. To maintain the system's integrity d. To allow unauthorized access 10. What is the ultimate goal of understanding the connection diagram of a fire detection and alarm system? a. Increase the chances of disastrous consequences b. Confuse occupants in case of emergencies c. Ensure the safety of building occupants d. Promptly initiate false alarms

“There’s No Such Thing as Sound Science” by By Christie Aschwanden was a lead science writer for FiveThirtyEight. FiveThirtyEight, Science, Dec. 6, 2017 Science is being turned against itself. For decades, its twin ideals of transparency and rigor have been weaponized by those who disagree with results produced by the scientific method. Under the Trump administration, that fight has ramped up again. In a move ostensibly meant to reduce conflicts of interest, Environmental Protection Agency Administrator Scott Pruitt has removed a number of scientists from advisory panels and replaced some of them with representatives from industries that the agency regulates. Like many in the Trump administration, Pruitt has also cast doubt on the reliability of climate science. For instance, in an interview with CNBC, Pruitt said that “measuring with precision human activity on the climate is something very challenging to do.” Similarly, Trump’s pick to head NASA, an agency that oversees a large portion the nation’s climate research, has insisted that research into human influence on climate lacks certainty, and he falsely claimed that “global temperatures stopped rising 10 years ago.” Kathleen Hartnett White, Trump’s nominee to head the White House Council on Environmental Quality, said in a Senate hearing last month that she thinks we “need to have more precise explanations of the human role and the natural role” in climate change. The same entreaties crop up again and again: We need to root out conflicts. We need more precise evidence. What makes these arguments so powerful is that they sound quite similar to the points raised by proponents of a very different call for change that’s coming from within science. This other movement strives to produce more robust, reproducible findings. Despite having dissimilar goals, the two forces espouse principles that look surprisingly alike: Science needs to be transparent. Results and methods should be openly shared so that outside researchers can independently reproduce and validate them. The methods used to collect and analyze data should be rigorous and clear, and conclusions must be supported by evidence. These are the arguments underlying an “open science” reform movement that was created, in part, as a response to a “reproducibility crisis” that has struck some fields of science.1 But they’re also used as talking points by politicians who are working to make it more difficult for the EPA and other federal agencies to use science in their regulatory decision-making, under the guise of basing policy on “sound science.” Science’s virtues are being wielded against it. What distinguishes the two calls for transparency is intent: Whereas the “open science” movement aims to make science more reliable, reproducible and robust, proponents of “sound science” have historically worked to amplify uncertainty, create doubt and undermine scientific discoveries that threaten their interests. “Our criticisms are founded in a confidence in science,” said Steven Goodman, co-director of the Meta-Research Innovation Center at Stanford and a proponent of open science. “That’s a fundamental difference — we’re critiquing science to make it better. Others are critiquing it to devalue the approach itself.” Calls to base public policy on “sound science” seem unassailable if you don’t know the term’s history. The phrase was adopted by the tobacco industry in the 1990s to counteract mounting evidence linking secondhand smoke to cancer. A 1992 Environmental Protection Agency report identified secondhand smoke as a human carcinogen, and Philip Morris responded by launching an initiative to promote what it called “sound science.” In an internal memo, Philip Morris vice president of corporate affairs Ellen Merlo wrote that the program was designed to “discredit the EPA report,” “prevent states and cities, as well as businesses from passing smoking bans” and “proactively” pass legislation to help their cause. The sound science tactic exploits a fundamental feature of the scientific process: Science does not produce absolute certainty. Contrary to how it’s sometimes represented to the public, science is not a magic wand that turns everything it touches to truth. Instead, it’s a process of uncertainty reduction, much like a game of 20 Questions. Any given study can rarely answer more than one question at a time, and each study usually raises a bunch of new questions in the process of answering old ones. “Science is a process rather than an answer,” said psychologist Alison Ledgerwood of the University of California, Davis. Every answer is provisional and subject to change in the face of new evidence. It’s not entirely correct to say that “this study proves this fact,” Ledgerwood said. “We should be talking instead about how science increases or decreases our confidence in something.” The tobacco industry’s brilliant tactic was to turn this baked-in uncertainty against the scientific enterprise itself. While insisting that they merely wanted to ensure that public policy was based on sound science, tobacco companies defined the term in a way that ensured that no science could ever be sound enough. The only sound science was certain science, which is an impossible standard to achieve. “Doubt is our product,” wrote one employee of the Brown & Williamson tobacco company in a 1969 internal memo. The note went on to say that doubt “is the best means of competing with the ‘body of fact’” and “establishing a controversy.” These strategies for undermining inconvenient science were so effective that they’ve served as a sort of playbook for industry interests ever since, said Stanford University science historian Robert Proctor. The sound science push is no longer just Philip Morris sowing doubt about the links between cigarettes and cancer. It’s also a 1998 action plan by the American Petroleum Institute, Chevron and Exxon Mobil to “install uncertainty” about the link between greenhouse gas emissions and climate change. It’s industry-funded groups’ late-1990s effort to question the science the EPA was using to set fine-particle-pollution air-quality standards that the industry didn’t want. And then there was the more recent effort by Dow Chemical to insist on more scientific certainty before banning a pesticide that the EPA’s scientists had deemed risky to children. Now comes a move by the Trump administration’s EPA to repeal a 2015 rule on wetlands protection by disregarding particular studies. (To name just a few examples.) Doubt merchants aren’t pushing for knowledge, they’re practicing what Proctor has dubbed “agnogenesis” — the intentional manufacture of ignorance. This ignorance isn’t simply the absence of knowing something; it’s a lack of comprehension deliberately created by agents who don’t want you to know, Proctor said.2 In the hands of doubt-makers, transparency becomes a rhetorical move. “It’s really difficult as a scientist or policy maker to make a stand against transparency and openness, because well, who would be against it?” said Karen Levy, researcher on information science at Cornell University. But at the same time, “you can couch everything in the language of transparency and it becomes a powerful weapon.” For instance, when the EPA was preparing to set new limits on particulate pollution in the 1990s, industry groups pushed back against the research and demanded access to primary data (including records that researchers had promised participants would remain confidential) and a reanalysis of the evidence. Their calls succeeded and a new analysis was performed. The reanalysis essentially confirmed the original conclusions, but the process of conducting it delayed the implementation of regulations and cost researchers time and money. Delay is a time-tested strategy. “Gridlock is the greatest friend a global warming skeptic has,” said Marc Morano, a prominent critic of global warming research and the executive director of ClimateDepot.com, in the documentary “Merchants of Doubt” (based on the book by the same name). Morano’s site is a project of the Committee for a Constructive Tomorrow, which has received funding from the oil and gas industry. “We’re the negative force. We’re just trying to stop stuff.” Some of these ploys are getting a fresh boost from Congress. The Data Quality Act (also known as the Information Quality Act) was reportedly written by an industry lobbyist and quietly passed as part of an appropriations bill in 2000. The rule mandates that federal agencies ensure the “quality, objectivity, utility, and integrity of information” that they disseminate, though it does little to define what these terms mean. The law also provides a mechanism for citizens and groups to challenge information that they deem inaccurate, including science that they disagree with. “It was passed in this very quiet way with no explicit debate about it — that should tell you a lot about the real goals,” Levy said. But what’s most telling about the Data Quality Act is how it’s been used, Levy said. A 2004 Washington Post analysis found that in the 20 months following its implementation, the act was repeatedly used by industry groups to push back against proposed regulations and bog down the decision-making process. Instead of deploying transparency as a fundamental principle that applies to all science, these interests have used transparency as a weapon to attack very particular findings that they would like to eradicate. Now Congress is considering another way to legislate how science is used. The Honest Act, a bill sponsored by Rep. Lamar Smith of Texas,3 is another example of what Levy calls a “Trojan horse” law that uses the language of transparency as a cover to achieve other political goals. Smith’s legislation would severely limit the kind of evidence the EPA could use for decision-making. Only studies whose raw data and computer codes were publicly available would be allowed for consideration. That might sound perfectly reasonable, and in many cases it is, Goodman said. But sometimes there are good reasons why researchers can’t conform to these rules, like when the data contains confidential or sensitive medical information.4 Critics, which include more than a dozen scientific organizations, argue that, in practice, the rules would prevent many studies from being considered in EPA reviews.5 It might seem like an easy task to sort good science from bad, but in reality it’s not so simple. “There’s a misplaced idea that we can definitively distinguish the good from the not-good science, but it’s all a matter of degree,” said Brian Nosek, executive director of the Center for Open Science. “There is no perfect study.” Requiring regulators to wait until they have (nonexistent) perfect evidence is essentially “a way of saying, ‘We don’t want to use evidence for our decision-making,’” Nosek said. Most scientific controversies aren’t about science at all, and once the sides are drawn, more data is unlikely to bring opponents into agreement. Michael Carolan, who researches the sociology of technology and scientific knowledge at Colorado State University, wrote in a 2008 paper about why objective knowledge is not enough to resolve environmental controversies. “While these controversies may appear on the surface to rest on disputed questions of fact, beneath often reside differing positions of value; values that can give shape to differing understandings of what ‘the facts’ are.” What’s needed in these cases isn’t more or better science, but mechanisms to bring those hidden values to the forefront of the discussion so that they can be debated transparently. “As long as we continue down this unabashedly naive road about what science is, and what it is capable of doing, we will continue to fail to reach any sort of meaningful consensus on these matters,” Carolan writes. The dispute over tobacco was never about the science of cigarettes’ link to cancer. It was about whether companies have the right to sell dangerous products and, if so, what obligations they have to the consumers who purchased them. Similarly, the debate over climate change isn’t about whether our planet is heating, but about how much responsibility each country and person bears for stopping it. While researching her book “Merchants of Doubt,” science historian Naomi Oreskes found that some of the same people who were defending the tobacco industry as scientific experts were also receiving industry money to deny the role of human activity in global warming. What these issues had in common, she realized, was that they all involved the need for government action. “None of this is about the science. All of this is a political debate about the role of government,” she said in the documentary. These controversies are really about values, not scientific facts, and acknowledging that would allow us to have more truthful and productive debates. What would that look like in practice? Instead of cherry-picking evidence to support a particular view (and insisting that the science points to a desired action), the various sides could lay out the values they are using to assess the evidence. For instance, in Europe, many decisions are guided by the precautionary principle — a system that values caution in the face of uncertainty and says that when the risks are unclear, it should be up to industries to show that their products and processes are not harmful, rather than requiring the government to prove that they are harmful before they can be regulated. By contrast, U.S. agencies tend to wait for strong evidence of harm before issuing regulations. Both approaches have critics, but the difference between them comes down to priorities: Is it better to exercise caution at the risk of burdening companies and perhaps the economy, or is it more important to avoid potential economic downsides even if it means that sometimes a harmful product or industrial process goes unregulated? In other words, under what circumstances do we agree to act on a risk? How certain do we need to be that the risk is real, and how many people would need to be at risk, and how costly is it to reduce that risk? Those are moral questions, not scientific ones, and openly discussing and identifying these kinds of judgment calls would lead to a more honest debate. Science matters, and we need to do it as rigorously as possible. But science can’t tell us how risky is too risky to allow products like cigarettes or potentially harmful pesticides to be sold — those are value judgements that only humans can make.

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