It's almost October which means more than just pumpkins, Halloween costumes, and candy. It means that it is the start of my annual FITober Challenge!
Let's face it, October can be hard on you. Starbucks is selling their Pumpkin Spice Latte, there is Halloween candy on every aisle of the grocery store and there are tons of festivals and parties to attend. That's why starting a fitness plan in October makes the perfect sense! The group will keep you super motivated and accountable to reach YOUR goals. We are going to Slim down in time for Halloween and keep it up through Thanksgiving and Christmas.
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Clean eating doesn't have be dull and boring. There are ways to add extra "sass" to your food so that your taste-buds stay happy while maintaining a healthy body.
Most store bought seasonings contain "extra" ingredients that are artificially made and not healthy. No sense in sabotaging all of that hard work with extra chemicals and sodium, those are things that are best to avoid. So why not make your own? These recipes are SO simple and take just a few minutes to put together. I double or even triple these recipes every time I make them so that I have enough to last for awhile.
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Check out these tips for QUICK and EASY ways to spice up your 21 DAY FIX CONTAINERS!
In the quest of reaching our full potential, which is our June focus, of course we have to talk about working on our bodies. Our challenge today is a Plank Challenge!
Plank are an awesome exercise move because it works all the muscles in your core, including the rectus abdominus (the "six-pack muscles" you can see), transverse abdominus, internal and external obliques, hips, and back. Planks help us stand upright & tall with good posture, improve balance & sports improvement and can also help with digestion & metabolism.
Plank Challenge: Hold a plank for one minute!
For proper form, your arms should be directly under the shoulders. Your entire body should be in a straight line from toes to head and the back completely flat, neither arched nor rounded. A slight pelvic tilt will help keep your back straight. Engage your core by pulling your belly button towards the spine, and hold.
You can also do these on your elbows or even drop to your knees. Whatever variation you decide to start with, just keep proper form and do your best!
Did you hold it longer than one minute?According to Wikipedia, "In April 2016 the world record for a front plank, resting on elbows, was set by former Marine officer and retired Drug Enforcement Administration (DEA) agent George Hood with a time of five hours, 15 minutes and 15 seconds. This was broken in May 2016 by Chinese policeman Mao Weidong who planked for eight hours, one minute and one second, who formerly held the record and regained it." I CANNOT EVEN IMAGINE DOING THIS!!!
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The BEST cookbook released today!! Have you heard about the 21 Day Fix workout that comes with the cute color coded containers? Well when you get the workout you get the containers and a small cook book/meal guide. The demand was there for MORE RECIPES!! So the trainer, Autumn Calabrese, created a whole cookbook with the 21 Day Fix containers, which allows you to eat healthy delicious foods and still lose weight!! Every recipe I've tried has been so good. You are going to LOVE this!
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Autumn Calabrese Presents FIXATE™—101 Personal Recipes to Use with the 21 Day Fix® Portion-Control Program takes a unique approach to healthy eating by making it simple to eat just the right amount of your favorite foods.
FIXATE and the Portion-Control Container Kit make it easy to use Autumn's simple system for measuring precise portions—you'll get 7 color-coded containers that go hand-in-hand with the 101 recipes in the FIXATEcookbook or to use with any of your favorite 21 Day Fix recipes. That way, you'll eat perfect portions of the delicious foods you crave while getting the nutrition you need to help you hit your fitness goals.
Easy-to-follow recipes (each marked with their color-coded container equivalents) designed to work with 21 Day Fix, 21 Day Fix EXTREME®, and Portion Fix™—or use the deliciously nutritious recipes to create balanced meals for any other Beachbody® program.
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Get Autumn's personal tips on preparing meals quickly and upgrading leftovers, so you can have delicious dishes even on your busiest days.
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Enjoy snacks, desserts, and the occasional cocktail—eating clean doesn't mean depriving yourself!
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Click to learn more about the 21 Day Fix and 21 Day Fix Extreme.


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An intelligent tutoring system (ITS)  is a computer system that aims to provide immediate and customized instruction or feedback to learners, usually without requiring intervention from a human teacher.  ITSs have the common goal of enabling learning in a meaningful and effective manner by using a variety of computing technologies.  There are many examples of ITSs being used in both formal education and professional settings in which they have demonstrated their capabilities and limitations.  There is a close relationship between intelligent tutoring, cognitive learning theories and design; and there is ongoing research to improve the effectiveness of ITS. An ITS typically aims to replicate the demonstrated benefits of one-to-one, personalized tutoring, in contexts where students would otherwise have access to one-to-many instruction from a single teacher (e.g., classroom lectures), or no teacher at all (e.g., online homework). ITSs are often designed with the goal of providing access to high quality education to each and every student.

History

Early mechanical systems

The possibility of intelligent machines has been discussed for centuries.  Blaise Pascal created the first calculating machine capable of mathematical functions in the 17th century simply called Pascal's Calculator. At this time the mathematician and philosopher Gottfried Wilhelm Leibniz envisioned machines capable of reasoning and applying rules of logic to settle disputes. These early works inspired later developments.

The concept of intelligent machines for instructional use date back as early as 1924, when Sidney Pressey of Ohio State University created a mechanical teaching machine to instruct students without a human teacher. His machine resembled closely a typewriter with several keys and a window that provided the learner with questions. The Pressey Machine allowed user input and provided immediate feedback by recording their score on a counter.

Pressey was influenced by Edward L. Thorndike, a learning theorist and educational psychologist at the Columbia University Teachers' College of the late 19th and early 20th centuries. Thorndike posited laws for maximizing learning.  Thorndike's laws included the law of effect, the law of exercise, and the law of recency.  By later standards, Pressey's teaching and testing machine would not be considered intelligent as it was mechanically run and was based on one question and answer at a time, but it set an early precedent for future projects.

By the 1950s and 1960s, new perspectives on learning were emerging. Burrhus Frederic "B.F." Skinner at Harvard University did not agree with Thorndike's learning theory of connectionism or Pressey's teaching machine.  Rather, Skinner was a behaviorist who believed that learners should construct their answers and not rely on recognition.  He too, constructed a teaching machine with an incremental mechanical system that would reward students for correct responses to questions.

Early electronic systems

In the period following the second world war, mechanical binary systems gave way to binary based electronic machines.  These machines were considered intelligent when compared to their mechanical counterparts as they had the capacity to make logical decisions. However, the study of defining and recognizing a machine intelligence was still in its infancy.

Alan Turing, a mathematician, logician and computer scientist, linked computing systems to thinking. One of his most notable papers outlined a hypothetical test to assess the intelligence of a machine which came to be known as the Turing test.  Essentially, the test would have a person communicate with two other agents, a human and a computer asking questions to both recipients.  The computer passes the test if it can respond in such a way that the human posing the questions cannot differentiate between the other human and the computer.  The Turing test has been used in its essence for more than two decades as a model for current ITS development.  The main ideal for ITS systems is to effectively communicate.  As early as the 1950s programs were emerging displaying intelligent features. Turing's work as well as later projects by researchers such as Allen Newell, Clifford Shaw, and Herb Simon showed programs capable of creating logical proofs and theorems. Their program, The Logic Theorist exhibited complex symbol manipulation and even generation of new information without direct human control and is considered by some to be the first AI program. Such breakthroughs would inspire the new field of Artificial Intelligence officially named in 1956 by John McCarthy at the Dartmouth Conference. This conference was the first of its kind that was devoted to scientists and research in the field of AI.

The latter part of the 1960s and 1970s saw many new CAI (Computer-Assisted instruction) projects that built on advances in computer science. The creation of the ALGOL programming language in 1958 enabled many schools and universities to begin developing Computer Assisted Instruction (CAI) programs. Major computer vendors and federal agencies in the US such as IBM, HP, and the National Science Foundation funded the development of these projects. Early implementations in education focused on programmed instruction (PI), a structure based on a computerized input-output system.  Although many supported this form of instruction,  there was limited evidence supporting its effectiveness. The programming language LOGO was created in 1967 by Wally Feurzeig, Cynthia Solomon, and Seymour Papert as a language streamlined for education. PLATO, an educational terminal featuring displays, animations, and touch controls that could store and deliver large amounts of course material, was developed by Donald Bitzer in the University of Illinois in the early 1970s. Along with these, many other CAI projects were initiated in many countries including the US, the UK, and Canada.

At the same time that CAI was gaining interest, Jaime Carbonell suggested that computers could act as a teacher rather than just a tool (Carbonell, 1970). A new perspective would emerge that focused on the use of computers to intelligently coach students called Intelligent Computer Assisted Instruction or Intelligent Tutoring Systems (ITS). Where CAI used a behaviourist perspective on learning based on Skinner's theories (Dede & Swigger, 1988), ITS drew from work in cognitive psychology, computer science, and especially artificial intelligence. There was a shift in AI research at this time as systems moved from the logic focus of the previous decade to knowledge based systems—systems could make intelligent decisions based on prior knowledge (Buchanan, 2006). Such a program was created by Seymour Papert and Ira Goldstein who created Dendral, a system that predicted possible chemical structures from existing data. Further work began to showcase analogical reasoning and language processing. These changes with a focus on knowledge had big implications for how computers could be used in instruction. The technical requirements of ITS, however, proved to be higher and more complex than CAI systems and ITS systems would find limited success at this time.

Towards the latter part of the 1970s interest in CAI technologies began to wane. Computers were still expensive and not as available as expected. Developers and instructors were reacting negatively to the high cost of developing CAI programs, the inadequate provision for instructor training, and the lack of resources.

Microcomputers and intelligent systems

The microcomputer revolution in the late 1970s and early 1980s helped to revive CAI development and jumpstart development of ITS systems. Personal computers such as the Apple 2, Commodore PET, and TRS-80 reduced the resources required to own computers and by 1981, 50% of US schools were using computers (Chambers & Sprecher, 1983). Several CAI projects utilized the Apple 2 as a system to deliver CAI programs in high schools and universities including the British Columbia Project and California State University Project in 1981.

The early 1980s would also see Intelligent Computer-Assisted Instruction (ICAI) and ITS goals diverge from their roots in CAI. As CAI became increasingly focused on deeper interactions with content created for a specific area of interest, ITS sought to create systems that focused on knowledge of the task and the ability to generalize that knowledge in non-specific ways (Larkin & Chabay, 1992). The key goals set out for ITS were to be able to teach a task as well as perform it, adapting dynamically to its situation. In the transition from CAI to ICAI systems, the computer would have to distinguish not only between the correct and incorrect response but the type of incorrect response to adjust the type of instruction. Research in Artificial Intelligence and Cognitive Psychology fueled the new principles of ITS. Psychologists considered how a computer could solve problems and perform 'intelligent' activities. An ITS programme would have to be able to represent, store and retrieve knowledge and even search its own database to derive its own new knowledge to respond to learner's questions. Basically, early specifications for ITS or (ICAI) require it to "diagnose errors and tailor remediation based on the diagnosis" (Shute & Psotka, 1994, p. 9).  The idea of diagnosis and remediation is still in use today when programming ITS.

A key breakthrough in ITS research was the creation of The LISP Tutor, a program that implemented ITS principles in a practical way and showed promising effects increasing student performance. The LISP Tutor was developed and researched in 1983 as an ITS system for teaching students the LISP programming language (Corbett & Anderson, 1992). The LISP Tutor could identify mistakes and provide constructive feedback to students while they were performing the exercise. The system was found to decrease the time required to complete the exercises while improving student test scores (Corbett & Anderson, 1992). Other ITS systems beginning to develop around this time include TUTOR created by Logica in 1984 as a general instructional tool and PARNASSUS created in Carnegie Mellon University in 1989 for language instruction.

Modern ITS
After the implementation of initial ITS, more researchers created a number of ITS for different students. In the late 20th century, Intelligent Tutoring Tools (ITTs) was developed by the Byzantium project, which involved six universities. The ITTs were general purpose tutoring system builders and many institutions had positive feedback while using them. (Kinshuk, 1996) This builder, ITT, would produce an Intelligent Tutoring Applet (ITA) for different subject areas. Different teachers created the ITAs and built up a large inventory of knowledge that was accessible by others through the Internet. Once an ITS was created, teachers could copy it and modify it for future use. This system was efficient and flexible. However, Kinshuk and Patel believed that the ITS was not designed from an educational point of view and was not developed based on the actual needs of students and teachers (Kinshuk and Patel, 1997).  Recent work has employed ethnographic and design research methods to examine the ways ITSs are actually used by students and teachers across a range of contexts, often revealing unanticipated needs that they meet, fail to meet, or in some cases, even create.

Modern day ITSs typically try to replicate the role of a teacher or a teaching assistant, and increasingly automate pedagogical functions such as problem generation, problem selection, and feedback generation. However, given a current shift towards blended learning models, recent work on ITSs has begun focusing on ways these systems can effectively leverage the complementary strengths of human-led instruction from a teacher or peer, when used in co-located classrooms or other social contexts.

There were three ITS projects that functioned based on conversational dialogue: AutoTutor, Atlas (Freedman, 1999), and Why2. The idea behind these projects was that since students learn best by constructing knowledge themselves, the programs would begin with leading questions for the students and would give out answers as a last resort. AutoTutor's students focused on answering questions about computer technology, Atlas's students focused on solving quantitative problems, and Why2's students focused on explaining physical systems qualitatively. (Graesser, VanLehn, and others, 2001) Other similar tutoring systems such as Andes (Gertner, Conati, and VanLehn, 1998) tend to provide hints and immediate feedback for students when students have trouble answering the questions. They could guess their answers and have correct answers without deep understanding of the concepts. Research was done with a small group of students using Atlas and Andes respectively. The results showed that students using Atlas made significant improvements compared with students who used Andes. However, since the above systems require analysis of students' dialogues, improvement is yet to be made so that more complicated dialogues can be managed.

Structure

Intelligent tutoring systems (ITSs) consist of four basic components based on a general consensus amongst researchers (Nwana,1990; Freedman, 2000; Nkambou et al., 2010):

The Domain model
The Student model
The Tutoring model, and
The User interface model
The domain model (also known as the cognitive model or expert knowledge model) is built on a theory of learning, such as the ACT-R theory which tries to take into account all the possible steps required to solve a problem. More specifically, this model "contains the concepts, rules, and problem-solving strategies of the domain to be learned. It can fulfill several roles: as a source of expert knowledge, a standard for evaluating the student's performance or for detecting errors, etc." (Nkambou et al., 2010, p. 4). Another approach for developing domain models is based on Stellan Ohlsson's Theory of Learning from performance errors, known as constraint-based modelling (CBM). In this case, the domain model is presented as a set of constraints on correct solutions.

The student model can be thought of as an overlay on the domain model. It is considered as the core component of an ITS paying special attention to student's cognitive and affective states and their evolution as the learning process advances. As the student works step-by-step through their problem solving process, an ITS engages in a process called model tracing. Anytime the student model deviates from the domain model, the system identifies, or flags, that an error has occurred. On the other hand, in constraint-based tutors the student model is represented as an overlay on the constraint set. Constraint-based tutors evaluate the student's solution against the constraint set, and identify satisfied and violated constraints. If there are any violated constraints, the student's solution is incorrect, and the ITS provides feedback on those constraints. Constraint-based tutors provide negative feedback (i.e. feedback on errors) and also positive feedback.

The tutor model accepts information from the domain and student models and makes choices about tutoring strategies and actions. At any point in the problem-solving process the learner may request guidance on what to do next, relative to their current location in the model. In addition, the system recognizes when the learner has deviated from the production rules of the model and provides timely feedback for the learner, resulting in a shorter period of time to reach proficiency with the targeted skills.  The tutor model may contain several hundred production rules that can be said to exist in one of two states, learned or unlearned.  Every time a student successfully applies a rule to a problem, the system updates a probability estimate that the student has learned the rule. The system continues to drill students on exercises that require effective application of a rule until the probability that the rule has been learned reaches at least 95% probability.

Knowledge tracing tracks the learner's progress from problem to problem and builds a profile of strengths and weaknesses relative to the production rules. The cognitive tutoring system developed by John Anderson at Carnegie Mellon University presents information from knowledge tracing as a skillometer, a visual graph of the learner's success in each of the monitored skills related to solving algebra problems. When a learner requests a hint, or an error is flagged, the knowledge tracing data and the skillometer are updated in real-time.

The user interface component "integrates three types of information that are needed in carrying out a dialogue: knowledge about patterns of interpretation (to understand a speaker) and action (to generate utterances) within dialogues; domain knowledge needed for communicating content; and knowledge needed for communicating intent" (Padayachee, 2002, p. 3).

Nkambou et al. (2010) make mention of Nwana's (1990) review of different architectures underlining a strong link between architecture and paradigm (or philosophy). Nwana (1990) declares, "[I]t is almost a rarity to find two ITSs based on the same architecture [which] results from the experimental nature of the work in the area" (p. 258). He further explains that differing tutoring philosophies emphasize different components of the learning process (i.e., domain, student or tutor). The architectural design of an ITS reflects this emphasis, and this leads to a variety of architectures, none of which, individually, can support all tutoring strategies (Nwana, 1990, as cited in Nkambou et al., 2010). Moreover, ITS projects may vary according to the relative level of intelligence of the components. As an example, a project highlighting intelligence in the domain model may generate solutions to complex and novel problems so
that students can always have new problems to work on, but it might only have simple methods for teaching those problems, while a system that concentrates on multiple or novel ways of teaching a particular topic might find a less sophisticated representation of that content sufficient.

Design and development methods

Apart from the discrepancy amongst ITS architectures each emphasizing different elements, the development of an ITS is much the same as any instructional design process. Corbett et al. (1997) summarized ITS design and development as consisting of four iterative stages: (1) needs assessment, (2) cognitive task analysis, (3) initial tutor implementation and (4) evaluation.

The first stage known as needs assessment is common to any instructional design process, especially software development.  This involves a learner analysis, consultation with subject matter experts and/or the instructor(s). This first step is part of the development of the expert/knowledge and student domain. The goal is to specify learning goals and to outline a general plan for the curriculum; it is imperative not to computerize traditional concepts but develop a new curriculum structure by defining the task in general and understanding learners' possible behaviours dealing with the task and to a lesser degree the tutor's behavior. In doing so, three crucial dimensions need to be dealt with: (1) the probability a student is able to solve problems; (2) the time it takes to reach this performance level and (3) the probability the student will actively use this knowledge in the future. Another important aspect that requires analysis is cost effectiveness of the interface. Moreover, teachers and student entry characteristics such as prior knowledge must be assessed since both groups are going to be system users.

The second stage, cognitive task analysis, is a detailed approach to expert systems programming with the goal of developing a valid computational model of the required problem solving knowledge. Chief methods for developing a domain model include: (1) interviewing domain experts, (2) conducting "think aloud" protocol studies with domain experts, (3) conducting "think aloud" studies with novices and (4) observation of teaching and learning behavior. Although the first method is most commonly used, experts are usually incapable of reporting cognitive components. The "think aloud" methods, in which the experts is asked to report aloud what s/he is thinking when solving typical problems, can avoid this problem. Observation of actual online interactions between tutors and students provides information related to the processes used in problem-solving, which is useful for building dialogue or interactivity into tutoring systems.

The third stage, initial tutor implementation, involves setting up a problem solving environment to enable and support an authentic learning process. This stage is followed by a series of evaluation activities as the final stage which is again similar to any software development project.

The fourth stage, evaluation includes (1) pilot studies to confirm basic usability and educational impact; (2) formative evaluations of the system under development, including (3) parametric studies that examine the effectiveness of system features and finally, (4) summative evaluations of the final tutor's effect: learning rate and asymptotic achievement levels.

A variety of authoring tools have been developed to support this process and create intelligent tutors, including ASPIRE, the Cognitive Tutor Authoring Tools (CTAT), GIFT, ASSISTments Builder and AutoTutor tools. The goal of most of these authoring tools is to simplify the tutor development process, making it possible for people with less expertise than professional AI programmers to develop Intelligent Tutoring Systems.

Eight principles of ITS design and development

Anderson et al. (1987) outlined eight principles for intelligent tutor design and Corbett et al. (1997) later elaborated on those principles highlighting an all-embracing principle which they believed governed intelligent tutor design, they referred to this principle as:

Principle 0: An intelligent tutor system should enable the student to work to the successful conclusion of problem solving.
 Represent student competence as a production set.
 Communicate the goal structure underlying the problem solving.
 Provide instruction in the problem solving context.
 Promote an abstract understanding of the problem-solving knowledge.
Minimize working memory load.
Provide immediate feedback on errors.
Adjust the grain size of instruction with learning.
Facilitate successive approximations to the target skill.

Use in practice

All this is a substantial amount of work, even if authoring tools have become available to ease the task. This means that building an ITS is an option only in situations in which they, in spite of their relatively high development costs, still reduce the overall costs through reducing the need for human instructors or sufficiently boosting overall productivity. Such situations occur when large groups need to be tutored simultaneously or many replicated tutoring efforts are needed. Cases in point are technical training situations such as training of military recruits and high school mathematics. One specific type of intelligent tutoring system, the Cognitive Tutor, has been incorporated into mathematics curricula in a substantial number of United States high schools, producing improved student learning outcomes on final exams and standardized tests. Intelligent tutoring systems have been constructed to help students learn geography, circuits, medical diagnosis, computer programming, mathematics, physics, genetics, chemistry, etc. Intelligent Language Tutoring Systems (ILTS), e.g. this one, teach natural language to first or second language learners. ILTS requires specialized natural language processing tools such as large dictionaries and morphological and grammatical analyzers with acceptable coverage.

Applications

During the rapid expansion of the web boom, new computer-aided instruction paradigms, such as e-learning and distributed learning, provided an excellent platform for ITS ideas. Areas that have used ITS include natural language processing, machine learning, planning, multi-agent systems, ontologies, Semantic Web, and social and emotional computing. In addition, other technologies such as  multimedia, object-oriented systems, modeling, simulation, and statistics have also been connected to or combined with ITS. Historically non-technological areas such as the educational sciences and psychology have also been influenced by the success of ITS.

In recent years, ITS has begun to move away from the search-based to include a range of practical applications. ITS have expanded across many critical and complex cognitive domains, and the results have been far reaching. ITS systems have cemented a place within formal education and these systems have found homes in the sphere of corporate training and organizational learning. ITS offers learners several affordances such as individualized learning, just in time feedback, and flexibility in time and space.

While Intelligent tutoring systems evolved from research in cognitive psychology and artificial intelligence, there are now many applications found in education and in organizations. Intelligent tutoring systems can be found in online environments or in a traditional classroom computer lab, and are used in K-12 classrooms as well as in universities. There are a number of programs that target mathematics but applications can be found in health sciences, language acquisition, and other areas of formalized learning.

Reports of improvement in student comprehension, engagement, attitude, motivation, and academic results have all contributed to the ongoing interest in the investment in and research of theses systems. The personalized nature of the intelligent tutoring systems affords educators the opportunity to create individualized programs. Within education there are a plethora of intelligent tutoring systems, an exhaustive list does not exist but several of the more influential programs are listed below.

Education

Algebra Tutor
PAT (PUMP Algebra Tutor or Practical Algebra Tutor) developed by the Pittsburgh Advanced Cognitive Tutor Center at Carnegie Mellon University, engages students in anchored learning problems and uses modern algebraic tools in order to engage students in problem solving and in sharing of their results. The aim of PAT is to tap into a students' prior knowledge and everyday experiences with mathematics in order to promote growth. The success of PAT is well documented (ex. Miami-Dade County Public Schools Office of Evaluation and Research) from both a statistical (student results) and emotional (student and instructor feedback) perspective.

SQL-Tutor is the first ever constraint-based tutor developed by the Intelligent Computer Tutoring Group (ICTG) at the University of Canterbury, New Zealand. SQL-Tutor teaches students how to retrieve data from databases using the SQL SELECT statement.

EER-Tutor is a constraint-based tutor (developed by ICTG) that teaches conceptual database design using the Entity Relationship model. An earlier version of EER-Tutor was KERMIT, a stand-alone tutor for ER modelling, which was shown to results in significant improvement of student's knowledge after one hour of learning (with the effect size of 0.6).

COLLECT-UML is a constraint-based tutor that supports pairs of students working collaboratively on UML class diagrams. The tutor provides feedback on the domain level as well as on collaboration.

StoichTutor is a web-based intelligent tutor that helps high school students learn chemistry, specifically the sub-area of chemistry known as stoichiometry. It has been used to explore a variety of learning science principles and techniques, such as worked examples and politeness.

Mathematics Tutor
The Mathematics Tutor (Beal, Beck & Woolf, 1998) helps students solve word problems using fractions, decimals and percentages.  The tutor records the success rates while a student is working on problems while providing subsequent, lever-appropriate problems for the student to work on. The subsequent problems that are selected are based on student ability and a desirable time in is estimated in which the student is to solve the problem.

eTeacher
eTeacher (Schiaffino et al., 2008) is an intelligent agent or pedagogical agent, that supports personalized e-learning assistance. It builds student profiles while observing student performance in online courses.  eTeacher then uses the information from the student's performance to suggest a personalized courses of action designed to assist their learning process.

ZOSMAT
ZOSMAT was designed to address all the needs of a real classroom. It follows and guides a student in different stages of their learning process. This is a student-centered ITS does this by recording the progress in a student's learning and the student program changes based on the student's effort. ZOSMAT can be used for either individual learning or in a real classroom environment alongside the guidance of a human tutor.

REALP
REALP was designed to help students enhance their reading comprehension by providing reader-specific lexical practice and offering personalized practice with useful, authentic reading materials gathered from the Web. The system automatically build a user model according to student's performance. After reading, the student is  given a series of exercises based on the target vocabulary found in reading.

CIRCSlM-Tutor
CIRCSIM_Tutor is an intelligent tutoring system that is used with first year medical students at the Illinois Institute of Technology.  It uses natural dialogue based, Socratic language to help students learn about regulating blood pressure.

Why2-Atlas
Why2-Atlas is an ITS that analyses students explanations of physics principles.  The students input their work in paragraph form and the program converts their words into a proof by making assumptions of student beliefs that are based on their explanations.  In doing this, misconceptions and incomplete explanations are highlighted.  The system then addresses these issues through a dialogue with the student and asks the student to correct their essay.  A number of iterations may take place before the process is complete.

SmartTutor
The University of Hong Kong (HKU) developed a SmartTutor to support the needs of continuing education students. Personalized learning was identified as a key need within adult education at HKU and SmartTutor aims to fill that need. SmartTutor provides support for students by combining Internet technology, educational research and artificial intelligence.

AutoTutor
AutoTutor assists college students in learning about computer hardware, operating systems and the Internet in an introductory computer literacy course by simulating the discourse patterns and pedagogical strategies of a human tutor.  AutoTutor attempts to understand learner's input from the keyboard and then formulate dialog moves with feedback, prompts, correction and hints.

ActiveMath
ActiveMath is a web-based, adaptive learning environment for mathematics. This system strives for improving long-distance learning, for complementing traditional classroom teaching, and for supporting individual and lifelong learning.

ESC101-ITS
The Indian Institute of Technology, Kanpur, India developed the ESC101-ITS, an intelligent tutoring system for introductory programming problems.

AdaptErrEx is an adaptive intelligent tutor that uses interactive erroneous examples to help students learn decimal arithmetic.

Corporate training and industry
Generalized Intelligent Framework for Tutoring (GIFT) is an educational software designed for creation of computer-based tutoring systems. Developed by the U.S. Army Research Laboratory from 2009 to 2011, GIFT was released for commercial use in May 2012. GIFT is open-source and domain independent, and can be downloaded online for free. The software allows an instructor to design a tutoring program that can cover various disciplines through adjustments to existing courses. It includes coursework tools intended for use by researchers, instructional designers, instructors, and students. GIFT is compatible with other teaching materials, such as PowerPoint presentations, which can be integrated into the program.

SHERLOCK
"SHERLOCK"  is used to train Air Force technicians to diagnose problems in the electrical systems of F-15 jets.  The ITS creates faulty schematic diagrams of  systems for the trainee to locate and diagnose.  The ITS provides diagnostic readings allowing the trainee to decide whether the fault lies in the circuit being tested or if it lies elsewhere in the system.  Feedback and guidance are provided by the system and help is available if requested.

Cardiac Tutor
The Cardiac Tutor's aim is to support advanced cardiac support techniques to medical personnel.  The tutor presents cardiac problems and, using a variety of steps, students must select various interventions. Cardiac Tutor provides clues, verbal advice, and feedback in order to personalize and optimize the learning. Each simulation, regardless of whether the students were successfully able to help their patients, results in a detailed report which students then review.

CODES
Cooperative Music Prototype Design is a Web-based environment for cooperative music prototyping. It was designed to support users, especially those who are not specialists in music, in creating musical pieces in a prototyping manner. The musical examples (prototypes) can be repeatedly tested, played and modified. One of the main aspects of CODES is interaction and cooperation between the music creators and their partners.

Effectiveness

Assessing the effectiveness of ITS programs is problematic. ITS vary greatly in design, implementation, and educational focus. When ITS are used in a classroom, the system is not only used by students, but by teachers as well. This usage can create barriers to effective evaluation for a number of reasons; most notably due to teacher intervention in student learning.

Teachers often have the ability to enter new problems into the system or adjust the curriculum. In addition, teachers and peers often interact with students while they learn with ITSs (e.g., during an individual computer lab session or during classroom lectures falling in between lab sessions) in ways that may influence their learning with the software. Prior work suggests that the vast majority of students' help-seeking behavior in classrooms using ITSs may occur entirely outside of the software - meaning that the nature and quality of peer and teacher feedback in a given class may be an important mediator of student learning in these contexts. In addition, aspects of classroom climate, such as students' overall level of comfort in publicly asking for help, or the degree to which a teacher is physically active in monitoring individual students may add additional sources of variation across evaluation contexts. All of these variables make evaluation of an ITS complex, and may help explain variation in results across evaluation studies.

Despite the inherent complexities, numerous studies have attempted to measure the overall effectiveness of ITS, often by comparisons of ITS to human tutors.  Reviews of early ITS systems (1995) showed an effect size of d = 1.0 in comparison to no tutoring, where as human tutors were given an effect size of d = 2.0. Kurt VanLehn's much more recent overview (2011) of modern ITS found that there was no statistical difference in effect size between expert one-on-one human tutors and step-based ITS. Some individual ITS have been evaluated more positively than others. Studies of the Algebra Cognitive Tutor found that the ITS students outperformed students taught by a classroom teacher on standardized test problems and real-world problem solving tasks.  Subsequent studies found that these results were particularly pronounced in students from special education, non-native English, and low-income backgrounds.

A more recent meta-analysis suggests that ITSs can exceed the effectiveness of both CAI and human tutors, especially when measured by local (specific) tests as opposed to standardized tests.  "Students who received intelligent tutoring outperformed students from conventional classes in 46 (or 92%) of the 50 controlled evaluations, and the improvement in performance was great enough to be considered of substantive importance in 39 (or 78%) of the 50 studies. The median ES in the 50 studies was 0.66, which is considered a moderate-to-large effect for studies in the social sciences. It is roughly equivalent to an improvement in test performance from the 50th to the 75th percentile. This is stronger than typical effects from other forms of tutoring. C.-L. C. Kulik and Kulik's (1991) meta-analysis, for example, found an average ES of 0.31 in 165 studies of CAI tutoring. ITS gains are about twice as high. The ITS effect is also greater than typical effects from human tutoring. As we have seen, programs of human tutoring typically raise student test scores about 0.4 standard deviations over control levels. Developers of ITSs long ago set out to improve on the success of CAI tutoring and to match the success of human tutoring. Our results suggest that ITS developers have already met both of these goals.... Although effects were moderate to strong in evaluations that measured outcomes on locally developed tests, they were much smaller in evaluations that measured outcomes on standardized tests. Average ES on studies with local tests was 0.73; average ES on studies with standardized tests was 0.13. This discrepancy is not unusual for meta-analyses that include both local and standardized tests... local tests are likely to align well with the objectives of specific instructional programs. Off-the-shelf standardized tests provide a looser fit. ... Our own belief is that both local and standardized tests provide important information about instructional effectiveness, and when possible, both types of tests should be included in evaluation studies."

Some recognized strengths of ITS are their ability to provide immediate yes/no feedback, individual task selection, on-demand hints, and support mastery learning.

Limitations

Intelligent tutoring systems are expensive both to develop and implement. The research phase paves the way for the development of systems that are commercially viable. However, the research phase is often expensive; it requires the cooperation and input of subject matter experts, the cooperation and support of individuals across both organizations and organizational levels. Another limitation in the development phase is the conceptualization and the development of software within both budget and time constraints. There are also factors that limit the incorporation of intelligent tutors into the real world, including the long timeframe required for development and the high cost of the creation of the system components. A high portion of that cost is a result of content component building. For instance, surveys revealed that encoding an hour of online instruction time took 300 hours of development time for tutoring content. Similarly, building the Cognitive Tutor took a ratio of development time to instruction time of at least 200:1 hours. The high cost of development often eclipses replicating the efforts for real world application.
Intelligent tutoring systems are not, in general, commercially feasible for real-world applications.

A criticism of Intelligent Tutoring Systems currently in use, is the pedagogy of immediate feedback and hint sequences that are built in to make the system "intelligent". This pedagogy is criticized for its failure to develop deep learning in students. When students are given control over the ability to receive hints, the learning response created is negative. Some students immediately turn to the hints before attempting to solve the problem or complete the task. When it is possible to do so, some students bottom out the hints – receiving as many hints as possible as fast as possible – in order to complete the task faster. If students fail to reflect on the tutoring system's feedback or hints,  and instead increase guessing until positive feedback is garnered, the student is, in effect, learning to do the right thing for the wrong reasons. Most tutoring systems are currently unable to detect shallow learning, or to distinguish between productive versus unproductive struggle (though see, e.g.,). For these and many other reasons (e.g., overfitting of underlying models to particular user populations), the effectiveness of these systems may differ significantly across users.

Another criticism of intelligent tutoring systems is the failure of the system to ask questions of the students to explain their actions. If the student is not learning the domain language than it becomes more difficult to gain a deeper understanding, to work collaboratively in groups, and to transfer the domain language to writing. For example, if the student is not "talking science" than it is argued that they are not being immersed in the culture of science, making it difficult to undertake scientific writing or participate in collaborative team efforts.  Intelligent tutoring systems have been criticized for being too "instructivist" and removing intrinsic motivation, social learning contexts, and context realism from learning.

Practical concerns, in terms of the inclination of the sponsors/authorities and the users to adapt intelligent tutoring systems, should be taken into account. First, someone must have a willingness to implement the ITS. Additionally an authority must recognize the necessity to integrate an intelligent tutoring software into current curriculum and finally, the sponsor or authority must offer the needed support through the stages of the system development until it is completed and implemented.

Evaluation of an intelligent tutoring system is an important phase; however, it is often difficult, costly, and time-consuming. Even though there are various evaluation techniques presented in the literature, there are no guiding principles for the selection of appropriate evaluation method(s) to be used in a particular context. Careful inspection should be undertaken to ensure that a complex system does what it claims to do. This assessment may occur during the design and early development of the system to identify problems and to guide modifications (i.e. formative evaluation). In contrast, the evaluation may occur after the completion of the system to support formal claims about the construction, behaviour of, or outcomes associated with a completed system (i.e. summative evaluation). The great challenge introduced by the lack of evaluation standards resulted in neglecting the evaluation stage in several existing ITS'.

Improvements
Intelligent tutoring systems are less capable than human tutors in the areas of dialogue and feedback. For example, human tutors are able to interpret the affective state of the student, and potentially adapt instruction in response to these perceptions. Recent work is exploring potential strategies for overcoming these limitations of ITSs, to make them more effective.

Dialogue

Human tutors have the ability to understand a person's tone and inflection within a dialogue and interpret this to provide continual feedback through an ongoing dialogue. Intelligent tutoring systems are now being developed to attempt to simulate natural conversations.  To get the full experience of dialogue there are many different areas in which a computer must be programmed; including being able to understand tone, inflection, body language, and facial expression and then to respond to these. Dialogue in an ITS can be used to ask specific questions to help guide students and elicit information while allowing students to construct their own knowledge. The development of more sophisticated dialogue within an ITS has been a focus in some current research partially to address the limitations and create a more constructivist approach to ITS. In addition, some current research has focused on modeling the nature and effects of various social cues commonly employed within a dialogue by human tutors and tutees, in order to build trust and rapport (which have been shown to have positive impacts on student learning).

Emotional affect

A growing body of work is considering the role of affect on learning, with the objective of developing intelligent tutoring systems  that can interpret and adapt to the different emotional states. Humans do not just use cognitive processes in learning but the affective processes they go through also plays an important role. For example, learners learn better when they have a certain level of disequilibrium (frustration), but not enough to make the learner feel completely overwhelmed. This has motivated affective computing to begin to produce and research creating intelligent tutoring systems that can interpret the affective process of an individual.  An ITS can be developed to read an individual's expressions and other signs of affect in an attempt to find and tutor to the optimal affective state for learning. There are many complications in doing this since affect is not expressed in just one way but in multiple ways so that for an ITS to be effective in interpreting affective states it may require a multimodal approach (tone, facial expression, etc...). These ideas have created a new field within ITS, that of Affective Tutoring Systems (ATS). One example of an ITS that addresses affect is Gaze Tutor which was developed to track students eye movements and determine whether they are bored or distracted and then the system attempts to reengage the student.

Rapport Building

To date, most ITSs have focused purely on the cognitive aspects of tutoring and not on the social relationship between the tutoring system and the student. As  demonstrated by the Computers are social actors paradigm humans often project social heuristics onto computers. For example, in observations of young children interacting with Sam the CastleMate, a collaborative story telling agent, children interacted with this simulated child in much the same manner as they would a human child. It has been suggested that to effectively design an ITS that builds rapport with students, the ITS should mimic strategies of instructional immediacy, behaviors which bridge the apparent social distance between students and teachers such as smiling and addressing students by name. With regard to teenagers, Ogan et al. draw from observations of close friends tutoring each other to argue that in order for an ITS to build rapport as a peer to a student, a more involved process of trust building is likely necessary which may ultimately require that the tutoring system possess the capability to effectively respond to and even produce seemingly rude behavior in order to mediate motivational and affective student factors through playful joking and taunting.

Teachable Agents

Traditionally ITSs take on the role of autonomous tutors, however they can also take on the role of tutees for the purpose of learning by teaching exercises. Evidence suggests that learning by teaching can be an effective strategy for mediating self-explanation, improving feelings of self-efficacy, and boosting educational outcomes and retention. In order to replicate this effect the roles of the student and ITS can be switched. This can be achieved by designing the ITS to have the appearance of being taught as is the case in the Teachable Agent Arithmetic Game  and Betty's Brain. Another approach is to have students teach a machine learning agent which can learn to solve problems by demonstration and correctness feedback as is the case in the APLUS system built with SimStudent. In order to replicate the educational effects of learning by teaching teachable agents generally have a social agent built on top of them which poses questions or conveys confusion. For example, Betty from Betty's Brain will prompt the student to ask her questions to make sure that she understands the material, and Stacy from APLUS will prompt the user for explanations of the feedback provided by the student.

See also
 Educational data mining
 Educational technology
 Evidence-based learning
 Learning objects
 Serious games
 Smart learning

References

Bibliography

Books

Papers
 Intelligent Tutoring Systems: An Historic Review in the Context of the Development of Artificial Intelligence and Educational Psychology
 Intelligent Tutoring Systems: The What and the How

 Intelligent Tutoring Systems: Using AI to Improve Training Performance and ROI
 A Framework for Model-Based Adaptive Training
 A Conceptual Framework for Internet based Intelligent Tutoring Systems
 Intelligent Tutoring Systems with Converersational Dialogue
 ELM-ART: An intelligent tutoring system on world wide web
 The defining characteristics of intelligent tutoring systems research: ITSs care, precisely
 Authoring Intelligent Tutoring Systems: An analysis of the state of the art
 Cognitive modeling and intelligent tutoring
 Intelligent Tutoring Goes To School in the Big City
 Adaptive Hypermedia: From Intelligent Tutoring Systems to Web-Based Education

External links
 The 11th International Conference on Intelligent Tutoring Systems – Co-adaptation in Learning – Chania (2012)
 The 10th International Conference on Intelligent Tutoring Systems – Bridges to Learning – Pittsburgh (2010)
 The 9th International Conference on Intelligent Tutoring Systems - Intelligent Tutoring Systems: Past and Future – Montreal (2008)
 The 8th International Conference on Intelligent Tutoring Systems (2006)
 The 2007 Artificial Intelligence in Education conference.
 MERLOT - Multimedia Educational Resource for Learning and Online Teaching
 A timeline of Teaching Machines http://teachingmachin.es/timeline.html

Educational technology

redpajama_set_name: RedPajamaWikipedia


This one keeps looking better and better!
You don't want to get in the way of these hackers.
And now I have the Digimon theme song stuck in my head...worth it.
Elevent Arts is giving fans another chance to catch the movie in theaters!
It's not too late to grab a ticket!
Time to battle once more with digital monsters!
A sneak peek of Digimon Adventure tri 3 will be shown during the first movie's U.S. theatrical premiere!
Joshua Seth returns as Tai in Digimon Adventure tri. – Chapter 1: Reunion!
Both old and new English voice actors join the cast of Digimon Adventure tri. – Chapter 1: Reunion.
The first film is coming, so hopefully that means the others will also.
An event in his honor will be held in Tokyo.
This game looks too good!


text:
Eophyllites is a genus of ammonoid cephalopods from the Lower Triassic and a predecessor of genera like Monophyllites and Ussurites.

The shell of Eophyllites is evolute, discoidal; whorls compressed, deeply embracing;  flanks gently convex, converging on a narrowly rounded venter. Sutures basically ceratitic; ventral lobe wide, divided by a high siphonal saddle; Lobesjagged, 1st lateral larger than the second; saddles monophyllic, smooth and rounded.

Related Palaeophyllites from the same age is ribbed on the outer flanks and lobes in the suture are more terminally digitate.

References

 W.J. Arkell, et al., 1957. Mesozoic Ammonoidea, Treatise on Invertebrate Paleontology, Part L. Geological Society of America and University of Kansas Press
 Sepkoski's list of Cephalopod Genera

Ammonitida genera
Triassic ammonites
Triassic animals of Asia


Ramadan is one of the five pillars of Islam, so it is an important time for every practising Muslim. It is a 30-day period of reflection and includes fasting in the hours between dawn and sunset. That means no food or water can pass the lips of a Muslim during those hours, with a few exceptions such as young children and the ill, until the end of Ramadan – called Eid al-Fitr.
The holy period falls in the ninth month of the Islamic calendar and its timing changes every year. In 2015, it starts on 18 June and falls during the English summer – meaning it could put extra pressure on those fasting because of the long, warm days. And there are additional prayers in the evening that can disrupt sleeping patterns for Britain's 2.78 million Muslims.
Long breaks between meals. Sleep disruptions. Hot weather, long days. How does it all affect Muslims at work?
Visaal Hussain, a Muslim, works for Sunderland University and law firm Brown Beer Nixon Mallon. It will be his first fast while working at the university. But Hussain, speaking in a personal capacity, tells IBTimes UK he knows "from past experience that it is a challenging feat".
The first few days are the most difficult because you have to adjust yourself in terms of only being able to eat and drink after sunset and before dawn.
After the first few days though I get used to it quite quickly as I have been fasting since I was about 11 [although it's only necessary to fast once you hit puberty and are mentally/physically healthy].
However with a lack of sleep it can be difficult to concentrate with work when you have to be up early, but towards noon that feeling begins to dissipate. Then about an hour before Iftar [the time at which the sun sets, the fast opens and we can eat/drink] the pangs of hunger do strike.
This year, the fasts last at least 19 hours and, as they fall within the summer months, thirst can be an issue at work. However, it's easily avoided by staying in a cool and shaded environment with reduced physical activity.
There are British laws against religious discrimination in the workplace. But European human rights law is also at play here. Though there are no specific cases involving Ramadan, a Christian British Airways employee brought one particularly high-profile religious discrimination case. BA had told her to take off her crucifix jewellery, which she challenged. She lost in a British court only for a European one to overturn the decision.
There may be reasonable grounds on which an employer draws a line. For example, an activity integral to the business but which allowances for a certain religious practice would compromise. But the law expects employers to be mindful of their religious staff. And firms must give evidence of why they cannot be if they choose not to accommodate their beliefs.
The basic principle is that somebody shouldn't be treated less favourably, so they shouldn't be treated to their detriment, because of their religion or religious belief.
So if someone is observing Ramadan they shouldn't be treated more detrimentally, less favourably, than anyone who isn't observing Ramadan. That's a primary concern.
Khaldoon Al Doory is corporate business development regional director for the Middle East at Ashridge Business School. He wrote a note on management best practice during Ramadan.
In it, Al Doory advises it is "considerate to offer an acknowledgement of a fasting colleague in workplaces".
"Managers could offer support, where possible, by being flexible about working hours, work duties and break times," Al Doory writes. "Managers often received high volumes of requests from Muslim staff to forgo their lunch breaks and leave earlier during Ramadan.
"Muslims also wish to pray more often during Ramadan, typically for a few minutes two or three times a day. This will normally be around 1.00pm and 4.20pm in June/July for a few minutes. Having a quiet and private space to pray is often very much appreciated."
Letting Muslim staff work through lunch so they can leave earlier is one compromise. Considering their needs for staff trips or celebrations would be another. For example, not taking everyone out for a work meal during Ramadan.
Muslims are not bending the rules by working night shifts either, even though it would mean sleeping through much of the fasting period during the day.
The fasting is only from dawn until sunset [...] The only thing is during the night there is the additional prayer which is offered in the mosques, which is a lengthy prayer in which the Quran is recited by specialist readers. But there's no reason a Muslim person cannot put in a night shift should that be the work schedule.
In terms of sleeping during the day while fasting, also there are no restrictions regarding that. A fasting person is allowed to sleep during the daytime. If for example they are on a 9-5 shift and they are home by 6pm, then they have at least another three hours and a bit to go until they break their fast. It is perfectly OK for them to go to sleep at 6pm and wake up in a couple of hours or so. Freshen up, do their prayer and get ready to break their fast at sunset.
So on both counts, no restrictions on sleeping in the day and no restrictions on working the night shift.
The important thing is dialogue. Employers should speak with their Muslim employees about Ramadan to iron out any issues because "there can't be a one-size-fits-all approach", Mogra says.
Each individual may have particular circumstances and they may express certain preferences. And if the company is able to accommodate those preferences, I'm sure they would be very much appreciated by the Muslim employee.
But they also acknowledge that it may not always be possible for their requests to be met. So it's a bit of give and take and accommodation in a way that the productivity of that Muslim employee does not diminish.
Just because we are fasting, it doesn't give us a reason to be lazy or less productive. The challenge is to be as productive as we would otherwise be even while we are fasting.
Find out if there are any concerns, especially because this year it's a particularly long day being in the summer. If there's going to be meetings, maybe schedule them for earlier on in the day rather than later on in the afternoon where their energy levels might be flagging.
Personally I see this blessed month as an opportunity to detoxify my mind, body and soul and use it as a stepping stone to enhance myself spiritually and grow closer to Allah (God), and strengthen my faith.
The sole purpose isn't to starve. A lot of Muslims, including myself, pray, read the Quran, study Islam and reflect upon life and those less fortunate around the world that don't have the luxuries of food and water. This is what Ramadan means to me.
My workplace have been brilliant with accommodating me. The firm and university have allowed me to start work at a later time and make up for the hours after usual closing hours. That is ideal for me as I believe I will be just as productive throughout the day.
This sort of understanding makes me want to work even harder. Kindness goes a long way.
When does month-long Muslim fast begin?


The Indie Summit 2019 Date: 8th - 10th May 2019 Location: The Rosewood Hotel Address: Jing Guang Centre, Hujialou, Chaoyang District, Beijing 100020, PRC, China. Click for map. After three successful years in London, the Indie Summit will move to Beijing, China, in 2019. Why? Because the Indie Summit is a global event. It's about the changes and global trends which affect all of us, all over the world. Europe and the US still drive a lot of global business – but we all know, we are living in the "Asian century." 60% of the world's population lives in Asia – 30% in China and India alone. Right now, the momentum is with China. It's not only a huge and critical market for many of your clients. It's also the source of many game-changing initiatives and advances in marketing and communications technology. Many leading figures from the companies involved, will be speaking at the Indie Summit 2019 – together with our usual world-class line-up of speakers from Europe, Asia, Africa and the Americas. Please join us to learn, share and exchange ideas together, in the most influential world city of the next ten years. What will happen? Two days of learning, sharing inspiration and networking, with world class expert speakers and the leaders of independent agencies from all around the world. Click here for a look at the 2018 Summit in London. Where will it be - and where can I stay? We hope you will find time to explore Beijing – The Forbidden City, the Great Wall of China, the Summer Palace... but everyone has told us, in Beijing it's best to hold a conference in a hotel. So the conference itself, and the evening networking events, will all take place at the Rosewood hotel. This includes: - The two day conference programme on Thursday 9th and Friday 10th May - A welcome cocktail and first-night dinner on Wednesday 8th evening in the Rosewood Pavilion, featuring specialities from Northern China - A gala dinner in the hotel ballroom on Thursday 9th evening featuring the best of what the hotel has to offer Right now, the Rosewood is THE most talked about new hotel in Beijing. Super-comfortable accommodation, the latest technology, the best food.. an experience in itself. And thanks to friends in China, we have negotiated a very advantageous rate for accommodation. So please – unless you live in Beijing, do stay at the hotel. Check the accommodation page for more details. Registration PLACES ARE LIMITED: RESERVE YOURS TODAY The Indie Summit is exclusively intended for agency leaders and a limited number of other invited guests, with a legitimate interest in the independent agency sector. A minimum of 80% of places are reserved for the Owners, CEO's and Senior Directors of independent marketing and communications agencies. The cost will be £1695 GBP and will include the full two day conference PLUS the evening networking events. Members who book before 30th November 2018 are entitled to a £300 GBP reduction on this rate of £1695 GBP. Please contact [email protected] for a discount code. The rate we have negotiated with the hotel assumes most delegates will also stay at the hotel for at least 2 nights. We will provide an exclusive link for you to book your accommodation at the special negotiated cost of CNY 1700 plus local tax per night for a deluxe room, for the nights of 8th and 9th May. (The rate will also be available before and after these dates, subject to the hotel's availability.) If you choose not to stay at the Rosewood for any reason, please let us know, as we will need to apply an additional charge of £250 GBP to your booking, to cover the increased fee we will need to pay to the hotel. If you are a permanent resident in Beijing, please contact [email protected] before booking your place, as special arrangements will apply. Agenda & Speakers Speakers for The Indie Summit 2019 will be announced soon. Meanwhile, click here for a reminder of the amazing people who spoke at the Indie Summit 2018. If you'd like to hear what they said, we'll send you a link to hear them again. Networking Participants at previous summits have all told us that the opportunity to meet and share experiences with leaders of other independent agencies from around the world, is one of the most important and rewarding aspects of any Indie Summit. Business relationships are established, friendships and partnerships are formed in a uniquely friendly atmosphere. This year there will be the added bonus of meeting some of our wonderful agency leaders from China. As the Asians say – "same-same but different!" If you are travelling with partners and (adult) family members, they are very welcome to join the evening events, especially the Gala dinner on Thursday evening. If you are staying before and after the conference, we'll be happy to recommend tourism activities and to hook you up with other conference delegates if you'd like company! Accommodation The venue for all the official conference activities and accommodation will be the Rosewood Hotel in Beijing, a stunning fusion of Chinese and Australian design, described by the London Daily Telegraph as "a cut above everywhere else in Beijing." The hotel is situated in the fashionable Chaoyang district, centrally located but with easy access out to the airport, and a short taxi ride from major Beijing locations like the Forbidden city and Tienamen Square. We have negotiated obtained a special rate for The Indie Summit participants, of CNY 1700 plus local tax per room per night for a deluxe room. At current exchange rates this is around US$ 250, or 215 Euros, or GB£ 190 a discount of 42% on the hotel's rack rate. If you choose to upgrade to more expensive room, this will also be available with a similar discount. If you stay a day or two either side of the conference, you can get the same rate, subject to the hotel's room availability. It's a very good deal! This rate is only available with a special link which we will send to you as soon as you book your delegate place. If you are travelling with family or other companions, the discount can be applied to their accommodation also. If you have any questions, please contact thenetworkone on +44 207 240 7117 or email [email protected] "The Rosewood is one of the capital's classiest lodgings, and a cut above everywhere else in Beijing. Chic guestrooms, on-trend restaurants and fabulous facilities are backed up by obsessive attention to detail – from the intriguing in-room book selection to the staff's designer uniforms." – Daily Telegraph, UK "If it is calm amid the hustle and bustle of Central Beijing you seek, then look no further than Sense spa. The relaxing treatments are just the tonic after a long day, and luxurious touches like bamboo linen (delightfully soft on the skin) are found throughout the serene space. The more active will enjoy the gym kitted out by Technogym, the yoga studio and the almost 80-foot-long pool." – Forbes Travel Guide, USA "staff are unfailingly friendly.. a bevy of chefs guide you through the local cuisine" – Mr and Mrs Smith, UK "No 1 hotel in China" – Conde Nast Traveller, Readers' Choice Awards 2017 Information Full conference payment is due at the time of booking and should be made via Eventbrite's secure credit card payment facility. No booking is confirmed until payment is received. Prices include Eventbrite's booking fee are as listed on the Eventbrite booking forms and exclude local taxes except where stated. In case you need to pay by any other means, please contact Stephanie Geisler at thenetworkone: [email protected] The cost will include all conference sessions, lunches and other refreshments, the welcome cocktail and dinner on Wednesday evening and the gala dinner on Thursday evening. Accommodation should be booked directly with the hotel, using the discount code which we will supply to you as soon as you have booked your conference place. Agency delegate bookings may only be made by, or on behalf of Owners and Senior Directors of independent marketing and communications agencies. thenetworkone reserves the right to decline bookings if in our judgment the delegate does not meet these criteria. If any booking is declined, the delegate will be informed individually and a full refund made, within two weeks. Speakers are advertised in good faith but thenetworkone cannot guarantee the appearance of any individual speaker. Thenetworkone reserves the right to make alterations to the Summit program content. Refunds are at the absolute discretion of thenetworkone and will normally only be offered in the event of the cancellation of the event, due to unavoidable reasons outside our control. Please note also, information below about visas. In case of cancellation of the event for any reason, thenetworkone's liability will be limited to the money received by thenetworkone from registered delegates, directly or via Eventbrite. However, a substitute delegate of similar seniority may attend the conference in place of the booked delegate, at no additional cost, subject to written confirmation provided by you and acknowledged by thenetworkone. You will receive a paper ticket to download and print. Please bring this with you to the conference, to speed your registration. In case you lose it or have problems printing it, please also bring photo ID for registration. Admission will be by delegate badge only, which you will receive when you register at the conference venue. Badges are valid for the named delegate only and must be worn at all times during the Summit. Thenetworkone reserves the right to refuse admission to any delegate who cannot provide evidence of registration. Visa Most visitors to China will require a visa. It is recommended to apply for a visa up to three months before the date of your intended entry into China. The application process is simple, but do not leave your application too late. If you require an invitation letter, thenetworkone will arrange this on request. If you apply in good time but are refused a visa for any reason, we will refund your delegate fee, providing you let us know at least one month before the start date of the conference. The Indie Summit organisers The Indie Summit is hosted by Thenetworkone Management Ltd, trading as thenetworkone: a world leading organization of independent marketing and communications agencies, working with more than 1,200 accredited agencies, in 109 countries worldwide. Once again, we are pleased to be collaborating with two highly professional partners: Eventbrite, a leading international ticketing and delegate registration company; and Blueprint Partners, an experienced London-based event production and management agency (and a member of thenetworkone). Frequently asked questions How many people from my agency can attend? We anticipate that most agencies will be represented by one or two Owners or Senior Directors. However, agencies may send additonal Senior delegates if they wish. Are substitutes allowed? If you have registered for the event and are unable to attend, please let us know. We can accept a substitute from your agency, providing he or she is also a senior director of the agency. There is no charge for this. What is your policy on refunds? There is no right to a refund except in case of the cancellation of the event or in case of the refusal of a visa, up to one month before the start of the conference. Thenetworkone may attempt to re-sell places to delegates who cannot attend, less an administration charge, if there is a waiting list. Is there an advantage to booking early? YES. WE RECOMMEND YOU BOOK NOW. Places are limited by the size of the conference theatre and we expect that the event will sell out. Each member agency of thenetworkone is guaranteed at least one delegate place, providing you book and pay by 30th November 2018. After this date, applications will be accepted on a "first come, first served" basis at the regular price of £1695 GBP. Do I need to register separately for the networking events? 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Director Jeremy Garelick Draws His Own Buzz for
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Director Jeremy Garelick Draws His Own Buzz for "The Wedding Ringer"
Comedic talents gain recognition at Variety Luncheon
Michelle Roe January 3, 2015 Arts & Entertainment 0 Comments
Director Jeremy Garelick (right) talks with "The Wedding Ringer" star Josh Gad.
Photos courtesy of Twitter
Jeremy Garelick, whose words have provided the one-liners to some of the funniest comedy films in recent years including The Hangover with Bradley Cooper and The Break Up with Vince Vaughn, has caught the attention of Hollywood's elite with his directorial debut in his film, The Wedding Ringer.
Garelick will make an appearance at the Palm Springs International Film Festival where he will be honored at Variety's "The 10 Directors to Watch" luncheon on Jan. 4 at the Parker Palm Springs.
Garelick hails from upstate New York and while he currently resides in L.A., the proud Dad of three says, "I love Palm Springs. It's a close getaway, but I feel like I'm on serious vacation here."
Garelick won't be resting much with several future projects in development, including Sick Day, a Universal film with Johnny Knoxville, a twisted R-rated version of Ferris Bueller, and The Insane Laws with Vince Vaughn.
Jeremy Garelick tweeted a photo working with photographer Mariana Antunano on "The Wedding Ringer".
"I am super honored to be amongst this crowd," Garelick says. "It was a real surprise because the other films feel like artsy, important, really good films, and I just wanted to make a funny movie to make me and a bunch of other people laugh."
No stranger to the comedy film genre, Garelick's talents shine in The Wedding Ringer, which is already creating a buzz prior to its Jan. 16 release. Palm Springs Life caught up with Garelick just before to his trip to the desert.
Would you say you are most comfortable in the comedic film genre?
"I think so. I love all movies and I enjoy watching non-comedies as well. But when I sit down and write stuff, comedy comes out. It's funny… the first script I ever wrote was a dark horror and thriller. And I gave it to a friend to read and he said, "It was the funniest script I ever read."
I read that you did a rewrite for The Hangover but were not credited at the time. How do you feel about this after the film franchise has been so successful?
"It, truthfully, was the most disappointing moment of my career, without a doubt…along with Todd Phillips, who was also not credited for writing. We took the original script idea and really did a massive rewrite and poured our heart into it. A lot of me, and Todd Phillips, went into that movie. So to have this (The Wedding Ringer) movie come now and the buzz is for me, a high point. I'm very excited."
Jeremy Garelick tweeted a photo with former NFL great Michael Strahan.
Was it difficult going from screenwriter to director?
"You know the reality is, I've always wanted to be a director. That's what I studied and what I've been working toward….I've been practicing and preparing for the opportunity (to direct) and I was able to achieve it. It was an awesome transition.
The Wedding Ringer is your feature film debut as a director. How does it compare to screenwriting?
"It's amazing to be able to see your vision all the way through and have your hands on (every single decision).
What was one of your biggest challenges as a director?
"Getting the movie green lit. It took almost 13 years to get this movie going with cast and different iterations of script. Trying to make the film for a certain budget and make it feel like it's much bigger film than what the budget allowed for…. I think we did a really good job. It feels like a big movie."
I understand you spent $25,000 of your own money to shoot a 6-minute scene from "The Pretender" to show you could direct.
"Yes, working with (the likes of) Joel Schumacher and Jerry Bruckheimer, I got to meet the best of the best in terms of the crew. I learned every aspect of making a film. I wanted to show that I could direct. I spent my own money and called in every favor."
This could have backfired. Why take that chance? Were you confident?
"I was pretty confident that I could nail that scene (in The Pretender). I felt ready to direct, so I didn't think it could backfire. I knew it would be funny on page and I had funny actors… (including The Hangover's Dr. Ken Jeong) so I knew it would be funny and I picked that scene to do because I knew it was a funny scene. For me, the worst-case scenario would be that (the experience) would be an amazing practice session. Like film school…you learn how to direct by going out there and doing it."
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